Skocz do pozycji: 1.

Tytuł:

Bainite transformation time model optimization for Austempered Ductile Iron with the use of heuristic algorithms

Autorzy:

Olejarczyk-Wożeńska, Izabela
Opaliński, Andrzej
Mrzygłód, Barbara
Regulski, Krzysztof
Kurowski, Wojciech

Powiązania:

https://bibliotekanauki.pl/articles/29520068.pdf

Data publikacji:

2022

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

heuristic optimization
bainite
ADI
Particle Swarm Optimization
Evolutionary Optimization Algorithm

Opis:

The paper presents the application of heuristic optimization methods in identifying the parameters of a model for bainite transformation time in ADI (Austempered Ductile Iron). Two algorithms were selected for parameter optimization – Particle Swarm Optimization and Evolutionary Optimization Algorithm. The assumption of the optimization process was to obtain the smallest normalized mean square error (objective function) between the time calculated on the basis of the identified parameters and the time derived from the experiment. As part of the research, an analysis was also made in terms of the effectiveness of selected methods, and the best optimization strategies for the problem to be solved were selected on their basis.

Źródło:

Computer Methods in Materials Science; 2022, 22, 3; 125-136
2720-4081
2720-3948

Pojawia się w:

Computer Methods in Materials Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 2.

Tytuł:

Population diversity maintenance in brain storm optimization algorithm

Autorzy:

Cheng, S.
Shi, Y.
Qin, Q.
Zhang, Q
Bai, R.

Powiązania:

https://bibliotekanauki.pl/articles/91571.pdf

Data publikacji:

2014

Wydawca:

Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych

Tematy:

brainstorm
optimization algorithm
convergence
divergence
brainstorm optimization
BSO
swarm intelligence
BSO algorithm

Opis:

The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm’s exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.

Źródło:

Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 2; 83-97
2083-2567
2449-6499

Pojawia się w:

Journal of Artificial Intelligence and Soft Computing Research

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 3.

Tytuł:

A novel merchant optimization algorithm for solving optimal reactive power problem

Autorzy:

Lenin, Kanagasabai

Powiązania:

https://bibliotekanauki.pl/articles/1837360.pdf

Data publikacji:

2021

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

optimal reactive power
transmission loss
merchant optimization algorithm

Opis:

In this paper Merchant Optimization Algorithm (MOA) is proposed to solve the optimal reactive power problem. Projected algorithm is modeled based on the behavior of merchants who gain in the market through various mode and operations. Grouping of the traders will be done based on their specific properties, and by number of candidate solution will be computed to individual merchant. First Group named as “Ruler candidate solution” afterwards its variable values are dispersed to the one more candidate solution and it named as “Serf candidate solution” In standard IEEE 14, 30, 57 bus test systems Merchant Optimization Algorithm (MOA) have been evaluated. Results show the proposed algorithm reduced power loss effectively.

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2021, 15, 1; 51-56
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 4.

Tytuł:

Evolutionary computing in operational research for two-layer neural networks

Autorzy:

Płaczek, S.

Powiązania:

https://bibliotekanauki.pl/articles/94935.pdf

Data publikacji:

2017

Wydawca:

Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie

Tematy:

evolutionary algorithm
neural network
optimization algorithm
mutation operator
crossover operator

Opis:

Considering the non-linear characteristics of the activation functions, the entire task is multidimensional and non-linear with a multimodal target function. Implementing evolutionary computing in the multimodal optimization tasks gives developers new and effective tools for seeking the global minimum. A developer has to find the optimal and simple transformation between the realization of a phenotype and a genotype. In the article, a two-layer neural network is analysed. In the first step, the population is created. In the main algorithm loop, a parent selection mechanism is used together with the fitness function. To evaluate the quality of evolutionary computing process different measured characteristics are used. The final results are depicted using charts and tables.

Źródło:

Information Systems in Management; 2017, 6, 2; 119-130
2084-5537
2544-1728

Pojawia się w:

Information Systems in Management

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 5.

Tytuł:

Algorytm optymalizacji parametrów eksploatacyjnych środków transportu
An optimization algorithm for exploitation parameters of means of transport

Autorzy:

Wojciechowski, Ł.
Cisowski, T.
Grzegorczyk, P.

Powiązania:

https://bibliotekanauki.pl/articles/312427.pdf

Data publikacji:

2010

Wydawca:

Instytut Naukowo-Wydawniczy "SPATIUM"

Tematy:

eksploatacja pojazdów
optymalizacja
algorytm optymalizacji
exploitation vehicles
optimization
optimization algorithm

Opis:

W artykule zaprezentowano algorytm wyznaczania optymalnych parametrów eksploatacyjnych dla środków transportu, oparty na programowaniu dynamicznym. Opisano w nim strukturę oraz zbiory danych algorytmu. Sformułowano i omówiono funkcję oraz podfunkcje celu, dotyczące parametrów eksploatacyjnych pojazdów. Przedstawiono istotę doboru warunków ograniczających jak i możliwości aplikacyjne opracowanego algorytmu.
The paper presents an algorithm for determination of optimal exploitation parameters of means of transport. The algorithm is based on dynamic programming. The paper discusses the structure as well as the data set for the algorithm. The function and subfunctions of the aim concerning exploitation parameters of vehicles were formed. Moreover, the selection of limiting conditions and application possibilities of the developed algorithm were discussed.

Źródło:

Autobusy : technika, eksploatacja, systemy transportowe; 2010, 11, 6
1509-5878
2450-7725

Pojawia się w:

Autobusy : technika, eksploatacja, systemy transportowe

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 6.

Tytuł:

Minimized Group Delay FIR Low Pass Filter Design Using Modified Differential Search Algorithm

Autorzy:

Prajapati, Sonelal
Rai, Sanjeev
Tiwari, Manish
Dwivedi, Atul Kumar

Powiązania:

https://bibliotekanauki.pl/articles/24200750.pdf

Data publikacji:

2023

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

differential search optimization algorithm
FIR filter
optimization
small group delay

Opis:

Designing a finite impulse response (FIR) filter with minimal group delay has proven to be a difficult task. Many research studies have focused on reducing pass band and stop band ripples in FIR filter design, often overlooking the optimization of group delay. While some works have considered group delay reduction, their approaches were not optimal. Consequently, the achievement of an optimal design for a filter with a low group delay value still remains a challenge. In this work, a modified differential search optimization algorithm has been used for the purpose of designing a minimal group delay FIR filter. The results obtained have been compared with the classical techniques and they turned out to be promising.

Źródło:

Journal of Telecommunications and Information Technology; 2023, 3; 78--84
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 7.

Tytuł:

FPGA-based secure and noiseless image transmission using lea and optimized bilateral filter

Autorzy:

Hebbale, Sunil B.
Akula, V.S. Giridhar
Baraki, Parashuram

Powiązania:

https://bibliotekanauki.pl/articles/27312891.pdf

Data publikacji:

2022

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

lightweight encryption algorithm
bilateral filter
whale optimization algorithm
discrete wavelet transform

Opis:

In today’s world, the transmission of secured and noiseless images is a difficult task. Therefore, effective strategies are important for securing data or secret images from attackers. Besides, denoising approaches are important for obtaining noise-free images. For this, an effective crypto-steganography method that is based on a lightweight encryption algorithm (LEA) and the modified least significant bit (MLSB) method for secured transmission is proposed. Moreover, a bilateral filter-based whale optimization algorithm (WOA) is used for image denoising. Before the image transmission, a secret image is encrypted by the LEA algorithm and embedded into the cover image using discrete wavelet transform (DWT) and MLSB techniques. After the image transmission, an extraction process is performed in order to recover the secret image. Finally, a bilateral WOA filter is used to remove the noise from the secret image. The Verilog code for the proposed model is designed and simulated in Xilinx software. Finally, the simulation results show that the proposed filtering technique results in performance that is superior to conventional bilateral and Gaussian filters in terms of the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM).

Źródło:

Computer Science; 2022, 23 (4); 451--466
1508-2806
2300-7036

Pojawia się w:

Computer Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 8.

Tytuł:

Timber wolf optimization algorithm for real power loss diminution

Autorzy:

Lenin, Kanagasabai

Powiązania:

https://bibliotekanauki.pl/articles/950973.pdf

Data publikacji:

2020

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

TWO algorithm
optimal reactive power
transmission loss
Timber Wolf optimization algorithm

Opis:

In this paper Timber Wolf optimization (TWO) algorithm is proposed to solve optimal reactive power problem. Timber Wolf optimization (TWO) algorithm is modeled based on the social hierarchy and hunting habits of Timber wolf towards finding prey. Based on their fitness values social hierarchy has been replicated by classifying the population of exploration agents. Exploration procedure has been modeled by imitating the hunting actions of timber wolf by using searching, encircling, and attacking the prey. There are three fittest candidate solutions embedded as α, β and γ to lead the population toward capable regions of the exploration space in each iteration of Timber Wolf optimization. Proposed Timber Wolf optimization (TWO) algorithm has been tested in standard IEEE 14, 30 bus test systems and simulation results show the projected algorithm reduced the real power loss efficiently.

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 24-28
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 9.

Tytuł:

A Novel Technique of Optimization for the COCOMO II Model Parameters using Teaching-Learning-Based Optimization Algorithm

Autorzy:

Khuat, T. T.
Le, M. H.

Powiązania:

https://bibliotekanauki.pl/articles/309064.pdf

Data publikacji:

2016

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

COCOMO II
cost estimation
NASA software
optimization
teaching-learning-based optimization algorithm

Opis:

Software cost estimation is a critical activity in the development life cycle for controlling risks and planning project schedules. Accurate estimation of the cost before the start-up of a project is essential for both the developers and the customers. Therefore, many models were proposed to address this issue, in which COCOMO II has been being widely employed in actual software projects. Good estimation models, such as COCOMO II, can avoid insufficient resources being allocated to a project. However, parameters for estimation formula in this model have not been optimized yet, and so the estimated results are not close to the actual results. In this paper, a novel technique to optimize the coefficients for COCOMO II model by using teaching-learning-based optimization (TLBO) algorithm is proposed. The performance of the model after optimizing parameters was tested on NASA software project dataset. The obtained results indicated that the improvement of parameters provided a better estimation capabilities compared to the original COCOMO II model.

Źródło:

Journal of Telecommunications and Information Technology; 2016, 1; 84-89
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 10.

Tytuł:

Inverse and direct optimization shape of airfoil using hybrid algorithm Big Bang-Big Crunch and Particle Swarm Optimization

Autorzy:

Masoumi, Heidar
Jalili, Farhad

Powiązania:

https://bibliotekanauki.pl/articles/281379.pdf

Data publikacji:

2019

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

hybrid optimization algorithm
airfoil
inverse and direct optimization approaches
Euler’s equations

Opis:

In this paper, Big Bang-Big Crunch and Particle Swarm Optimization algorithms are combined and used for the first time to optimize airfoil geometry as a aerodynamic cross section. The optimization process is carried out both in reverse and direct directions. In the reverse approach, the object function is the difference between pressure coefficients of the optimized and target airfoils, which must be minimized. In the direct approach, three objective functions are introduced, the first of which is the drag to lift (D/L) ratio. It is minimized considering four different initial geometries, ultimately, all four geometries converge to the same final geometry. In other cases, maximizing lift the coefficient with the fixed drag coefficient constraint and minimizing the drag coefficient while the lift coefficient is fixed are defined as purposes. The results show that by changing the design parameters of the initial airfoil geometry, the proposed hybrid optimization algorithm as a powerful method satisfies the needs with proper accuracy and finally reaches the desired geometry.

Źródło:

Journal of Theoretical and Applied Mechanics; 2019, 57, 3; 697-711
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 11.

Tytuł:

Optimization of Square-shaped Bolted Joints Based on Improved Particle Swarm Optimization Algorithm

Autorzy:

Chen, Kui
Yang, Cheng
Zhao, Yongsheng
Niu, Peng
Niu, NaNa
Hongchao, Wu

Powiązania:

https://bibliotekanauki.pl/articles/27312779.pdf

Data publikacji:

2023

Wydawca:

Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN

Tematy:

particle swarm optimization algorithm
bolt connection
bolted joint
fractal theory

Opis:

The bolted joint is widely used in heavy-duty CNC machine tools, which has huge influence on working precision and overall stiffness of CNC machine. The process parameters of group bolt assembly directly affect the stiffness of the connected parts. The dynamic model of bolted joints is established based on the fractal theory, and the overall stiffness of joint surface is calculated. In order to improve the total stiffness of bolted assembly, an improved particle swarm optimization algorithm with combination of time-varying weights and contraction factor is proposed. The input parameters are preloading of bolts, fractal dimension, roughness, and object thickness. The main goal is to maximize the global rigidity. The optimization results show that improved algorithm has better convergence, faster calculation speed, preferable results, and higher optimization performance than standard particle swarm optimization algorithm. Moreover, the global rigidity optimization is achieved.

Źródło:

Eksploatacja i Niezawodność; 2023, 25, 3; art. no. 168487
1507-2711

Pojawia się w:

Eksploatacja i Niezawodność

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 12.

Tytuł:

Active power loss reduction by novel feral cat swarm optimization algorithm

Autorzy:

Lenin, Kanagasabai

Powiązania:

https://bibliotekanauki.pl/articles/384742.pdf

Data publikacji:

2020

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

optimal reactive power
Transmission loss
Feral Cat Swarm Optimization Algorithm

Opis:

In this paper Feral Cat Swarm Optimization (FCS) Algorithm is proposed to solve optimal reactive power problem. Projected methodology has been modeled based on the activities of the feral cats. They have two main phases primarily “seeking mode”, “tracing mode”. In the proposed FCS algorithm, population of feral cats are created and arbitrarily scattered in the solution space, with every feral cat representing a solution. Produced population is alienated into two subgroups. One group will observe their surroundings which come under the seeking mode and another group moving towards the prey which will come under the tracing mode. New-fangled positions, fitness functions will be calculated subsequent to categorization of feral cats for seeking mode and tracing mode, through that cat with the most excellent solution will be accumulated in the memory. Feral Cat Swarm Optimization (FCS) Algorithm has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 2; 25-29
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 13.

Tytuł:

Resource Allocation Optimization in Critical Chain Method

Autorzy:

Pawiński, G.
Sapiecha, K.

Powiązania:

https://bibliotekanauki.pl/articles/106140.pdf

Data publikacji:

2012

Wydawca:

Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej

Tematy:

Critical Chain Project Management
CCPM
resource allocation
optimization algorithm
RCPSP

Opis:

The paper presents resource allocation optimization in Critical Chain Project Management (CCPM). The cheapest project schedule is searched with respect to time constraints. The algorithm originally developed for the hardware-software co-design of heterogeneous distributed systems is adapted to work with human resources and CCPM method. The results of the optimization showed significant efficiency of the algorithm in comparison with a greedy algorithm. On average, the optimization gives 14.10% of cost reduction using the same number of resources. The gain varies depending on the number of resources and the time constraints. Advantages and disadvantages of such an approach are also discussed.

Źródło:

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2012, 12, 1; 17-29
1732-1360
2083-3628

Pojawia się w:

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 14.

Tytuł:

Passivity-based optimal control of discrete-time nonlinear systems

Autorzy:

Binazadeh, T.
Shafiei, M. H.

Powiązania:

https://bibliotekanauki.pl/articles/205917.pdf

Data publikacji:

2013

Wydawca:

Polska Akademia Nauk. Instytut Badań Systemowych PAN

Tematy:

nonlinear discrete-time systems optimal passivity-based control
genetic optimization algorithm

Opis:

In this paper, a passivity-based optimal controlmethod for a broad class of nonlinear discrete-time systems is proposed. The resulting control law is a static output feedback law which is practically preferred with respect to the state feedback law and is simple to implement. The control law has a general structure with adjustable parameters which are tuned, using an optimization method (genetic algorithm), to minimize an arbitrary cost function. By choosing this cost function it is possible to shape the transient response of the closed-loop system, as it is desirable. An illustrative ex ample shows the effectiveness of the proposed approach.

Źródło:

Control and Cybernetics; 2013, 42, 3; 627-637
0324-8569

Pojawia się w:

Control and Cybernetics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 15.

Tytuł:

Stochastic fractal based multiobjective fruit fly optimization

Autorzy:

Zuo, C.
Wu, L.
Zeng, Z. F.
Wei, H. L.

Powiązania:

https://bibliotekanauki.pl/articles/330026.pdf

Data publikacji:

2017

Wydawca:

Uniwersytet Zielonogórski. Oficyna Wydawnicza

Tematy:

multiobjective optimization
fruit fly optimization algorithm
stochastic fractal
optymalizacja wielokryterialna
algorytm optymalizacji
fraktal stochastyczny

Opis:

The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve the convergence performance of the fruit fly optimization algorithm. To deal with multiobjective optimization problems, the Pareto domination concept is integrated into the selection process of fruit fly optimization and a novel multiobjective fruit fly optimization algorithm is then developed. Similarly to most of other multiobjective evolutionary algorithms (MOEAs), an external elitist archive is utilized to preserve the nondominated solutions found so far during the evolution, and a normalized nearest neighbor distance based density estimation strategy is adopted to keep the diversity of the external elitist archive. Eighteen benchmarks are used to test the performance of the stochastic fractal based multiobjective fruit fly optimization algorithm (SFMOFOA). Numerical results show that the SFMOFOA is able to well converge to the Pareto fronts of the test benchmarks with good distributions. Compared with four state-of-the-art methods, namely, the non-dominated sorting generic algorithm (NSGA-II), the strength Pareto evolutionary algorithm (SPEA2), multi-objective particle swarm optimization (MOPSO), and multiobjective self-adaptive differential evolution (MOSADE), the proposed SFMOFOA has better or competitive multiobjective optimization performance.

Źródło:

International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 417-433
1641-876X
2083-8492

Pojawia się w:

International Journal of Applied Mathematics and Computer Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 16.

Tytuł:

Fast bearing fault diagnosis of rolling element using Lévy Moth-Flame optimization algorithm and Naive Bayes

Autorzy:

Sun, Shuang
Przystupa, Krzysztof
Wei, Ming
Yu, Han
Ye, Zhiwei
Kochan, Orest

Powiązania:

https://bibliotekanauki.pl/articles/1841936.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN

Tematy:

malfunction diagnostics
naive Bayes
moth-flame optimization algorithm
ensemble empirical mode decomposition

Opis:

Fault diagnosis is part of the maintenance system, which can reduce maintenance costs, increase productivity, and ensure the reliability of the machine system. In the fault diagnosis system, the analysis and extraction of fault signal characteristics are very important, which directly affects the accuracy of fault diagnosis. In the paper, a fast bearing fault diagnosis method based on the ensemble empirical mode decomposition (EEMD), the moth-flame optimization algorithm based on Lévy flight (LMFO) and the naive Bayes (NB) is proposed, which combines traditional pattern recognition methods meta-heuristic search can overcome the difficulty of selecting classifier parameters while solving small sample classification under reasonable time cost. The article uses a typical rolling bearing system to test the actual performance of the method. Meanwhile, in comparison with the known algorithms and methods was also displayed in detail. The results manifest the efficiency and accuracy of signal sparse representation and fault type classification has been enhanced.

Źródło:

Eksploatacja i Niezawodność; 2020, 22, 4; 730-740
1507-2711

Pojawia się w:

Eksploatacja i Niezawodność

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 17.

Tytuł:

Falcon optimization algorithm for bayesian network structure learning

Autorzy:

Kareem, Shahab Wahhab
Okur, Mehmet Cudi

Powiązania:

https://bibliotekanauki.pl/articles/2097968.pdf

Data publikacji:

2021

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

Bayesian network
global search
falcon optimization algorithm
structure learning
search and score

Opis:

In machine-learning, some of the helpful scientific models during the production of a structure of knowledge are Bayesian networks. They can draw the relationships of probabilistic dependency among many variables. The score and search method is a tool that is used as a strategy for learning the structure of a Bayesian network. The authors apply the falcon optimization algorithm (FOA) to the learning structure of a Bayesian network. This paper has employed reversing, deleting, moving, and inserting to obtain the FOA for approaching the optimal solution of a structure. Essentially, the falcon prey search strategy is used in the FOA algorithm. The result of the proposed technique is associated with pigeon-inspired optimization, greedy search, and simulated annealing that apply the BDeu score function. The authors have also examined the performances of the confusion matrix of these techniques by utilizing several benchmark data sets. As shown by the experimental evaluations, the proposed method has a more reliable performance than other algorithms (including the production of excellent scores and accuracy values).

Źródło:

Computer Science; 2021, 22 (4); 553--569
1508-2806
2300-7036

Pojawia się w:

Computer Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 18.

Tytuł:

Optimal sliding mode controller design based on whale optimization algorithm for lower limb rehabilitation robot

Autorzy:

Sabah, Noor
Hameed, Ekhlas
Al-Huseiny, Muayed S

Powiązania:

https://bibliotekanauki.pl/articles/1956062.pdf

Data publikacji:

2021

Wydawca:

Polskie Towarzystwo Promocji Wiedzy

Tematy:

Optimal Sliding Mode Controller
Whale Optimization Algorithm
lower limb
rehabilitation robot
kończyna dolna
robot rehabilitacyjny

Opis:

The Sliding Mode Controllers (SMCs) are considered among the most common stabilizer and controllers used with robotic systems due to their robust nonlinear scheme designed to control nonlinear systems. SMCs are insensitive to external disturbance and system parameters variations. Although the SMC is an adaptive and model-based controller, some of its values need to be determined precisely. In this paper, an Optimal Sliding Mode Controller (OSMC) is suggested based on Whale Optimization Algorithm (WOA) to control a two-link lower limb rehabilitation robot. This controller has two parts, the equivalent part, and the supervisory controller part. The stability assurance of the controlled rehabilitation robot is analyzed based on Lyapunov stability. The WO algorithm is used to determine optimal parameters for the suggested SMC. Simulation results of two tested trajectories (linear step signal and nonlinear sine signal) demonstrate the effectiveness of the suggested OSMC with fast response, very small overshoot, and minimum steady-state error.

Źródło:

Applied Computer Science; 2021, 17, 3; 47-59
1895-3735

Pojawia się w:

Applied Computer Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 19.

Tytuł:

Implementation of gravity model to estimation of transportation market shares
Obszary przewagi konkurencyjnej na rynku usług transportowych

Autorzy:

Krata, P.

Powiązania:

https://bibliotekanauki.pl/articles/224208.pdf

Data publikacji:

2010

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

usługi transportowe
transport
konkurencyjność
przedsiębiorstwo transportowe
algorytm optymalizacji
transport market
competitiveness
transport enterprises
optimization algorithm

Opis:

The theoretical consideration presented in the paper is inspired by market gravity models, as an interesting attitude towards operations research on a market. The transportation market issues are emphasized. The mathematical model of relations, taking place between transportation companies and their customers on the market, which is applied in the course of the research is based on continuous functions characteristics. This attitude enables the use of the field theory notions. The resultant vector-type utility function facilitates obtaining of competitive advantage areas for all transportation companies located on the considered transportation market.
Prezentowane dociekania teoretyczne inspirowane są teorią grawitacji rynkowej, jako interesującym elementem badań rynkowych. Rozważaniom poddano rynek usług transportowych. Zastosowany został model relacji zachodzących pomiędzy przedsiębiorstwami transportowymi i ich klientami na rynku usług transportowych, wykorzystujący do opisu cech przedsiębiorstw i klientów funkcje ciągłe o charakterze lokalnym. Umożliwiło to aplikację wybranych elementów matematycznej teorii pola. Wykorzystana wektorowa funkcja użyteczności posłużyła do wyznaczania obszarów przewagi konkurencyjnej poszczególnych przedsiębiorstw transportowych na rynku usług transportowych, przy zastosowaniu zaproponowanego algorytmu optymalizacyjnego.

Źródło:

Archives of Transport; 2010, 22, 1; 83-96
0866-9546
2300-8830

Pojawia się w:

Archives of Transport

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 20.

Tytuł:

A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

Autorzy:

Mostafa, Hazem H.
Ibrahim, Amr M.
Anis, Wagdi R.

Powiązania:

https://bibliotekanauki.pl/articles/141645.pdf

Data publikacji:

2019

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

hybrid optimization
golden sections search
multi-verse optimization algorithm
maximum power point tracking
perturb and observe
photovoltaic (PV)

Opis:

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS- PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.

Źródło:

Archives of Electrical Engineering; 2019, 68, 3; 611-627
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 21.

Tytuł:

Design of a Predictive PID Controller Using Particle Swarm Optimization

Autorzy:

Mustafa, Norhaida
Hashim, Fazida Hanim

Powiązania:

https://bibliotekanauki.pl/articles/1844451.pdf

Data publikacji:

2020

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

proportional integral derivative controller
particle swarm optimization (PSO) algorithm
optimization
predictive PID

Opis:

The proportional-integral-derivative (PID) controller is widely used in various industrial applications such as process control, motor drives, magnetic and optical memory, automotive, flight control and instrumentation. PID tuning refers to the generation of PID parameters (Kp, Ki, Kd) to obtain the optimum fitness value for any system. The determination of the PID parameters is essential for any system that relies on it to function in a stable mode. This paper proposes a method in designing a predictive PID controller system using particle swarm optimization (PSO) algorithm for direct current (DC) motor application. Extensive numerical simulations have been done using the Mathwork’s Matlab simulation environment. In order to gain full benefits from the PSO algorithm, the PSO parameters such as inertia weight, iteration number, acceleration constant and particle number need to be carefully adjusted and determined. Therefore, the first investigation of this study is to present a comparative analysis between two important PSO parameters; inertia weight and number of iteration, to assist the predictive PID controller design. Simulation results show that inertia weight of 0.9 and iteration number 100 provide a good fitness achievement with low overshoot and fast rise and settling time. Next, a comparison between the performance of the DC motor with PID-PSO, with PID of gain 1, and without PID were also discussed. From the analysis, it can be concluded that by tuning the PID parameters using PSO method, the best gain in performance may be found. Finally, when comparing between the PID-PSO and its counterpart, the PI-PSO, the PID-PSO controller gives better performance in terms of robustness, low overshoot (0.005%), low minimum rise time (0.2806 seconds) and low settling time (0.4326 seconds).

Źródło:

International Journal of Electronics and Telecommunications; 2020, 66, 4; 737-743
2300-1933

Pojawia się w:

International Journal of Electronics and Telecommunications

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 22.

Tytuł:

Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm

Autorzy:

Yilmaz, Mehmet
Dede, Tayfun
Grzywiński, Maksym

Powiązania:

https://bibliotekanauki.pl/articles/31342511.pdf

Data publikacji:

2023

Wydawca:

Politechnika Częstochowska

Tematy:

multi-objective optimization
grey wolf optimization algorithm
time-cost-risk
optymalizacja wielocelowa
algorytm optymalizacji szarego wilka
czas-koszt-ryzyko

Opis:

Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.

Źródło:

Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2023, 12; 79-86
2299-8535
2544-963X

Pojawia się w:

Budownictwo o Zoptymalizowanym Potencjale Energetycznym

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 23.

Tytuł:

An algorithm for comprehensive optimization of navigation as a tool to improve safety and reduce the operating costs of vessels
Algorytm ułatwiający optymalizację prowadzenia statku, jako narzędzie służące poprawie bezpieczeństwa i obniżeniu kosztów eksploatacyjnych statków

Autorzy:

Pleskacz, K.

Powiązania:

https://bibliotekanauki.pl/articles/311423.pdf

Data publikacji:

2016

Wydawca:

Instytut Naukowo-Wydawniczy "SPATIUM"

Tematy:

martime transport
safety in martime transport
optimization algorithm
transport morski
bezpieczeństwo transportu morskiego
algorytm oceny optymalizacji

Opis:

Currently being developed system based on objective, scientific knowledge about the risks in transport. The author presents the foundation of an integrated assessment of the optimization algorithm as a tool to improve safety and reduce operating costs in maritime transport. The algorithm proposed can be applied to all types of vessels operating around the world but the amount of saving can be estimated only by carrying out a comprehensive study and simulation in a virtual world where digital mock-ups can be used to explore various relationships and configurations. Therefore, the author proposes the creation of a navigation optimization assessment centre as a place of research and broader education related to use of the developed algorithm.
Obecnie opracowywane są systemy bazujące na obiektywnej, naukowej wiedzy o ryzyku w transporcie. Autor prezentuje założenia zintegrowanego algorytmu oceny optymalizacji, jako narzędzia służącego poprawie bezpieczeństwa i obniżenia kosztów eksploatacyjnych w transporcie morskim. Proponowany algorytm można zastosować dla wszystkich typów statków operujących na całym świecie, ale wielkość oszczędności można oszacować jedynie prowadząc kompleksowe badania symulacyjne, a w przyszłości przejść do świata wirtualnego, gdzie poprzez zastosowanie makiet cyfrowych badać różne zależności i konfiguracje. Dlatego autor proponuje utworzenie centrum oceny optymalizacji nawigacji, jako miejsca prowadzenia badań i szeroko pojętej edukacji związanej z użytkowaniem opracowanego algorytmu.

Źródło:

Autobusy : technika, eksploatacja, systemy transportowe; 2016, 17, 6; 675-678
1509-5878
2450-7725

Pojawia się w:

Autobusy : technika, eksploatacja, systemy transportowe

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 24.

Tytuł:

Adaptive Rider Feedback Artificial Tree Optimization-Based Deep Neuro-Fuzzy Network for Classification of Sentiment Grade

Autorzy:

Jasti, Sireesha
Kumar, G.V.S. Raj

Powiązania:

https://bibliotekanauki.pl/articles/2200961.pdf

Data publikacji:

2023

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

deep learning network
feedback artificial tree
natural language processing (NLP)
rider optimization algorithm
sentiment grade classification

Opis:

Sentiment analysis is an efficient technique for expressing users’ opinions (neutral, negative or positive) regarding specific services or products. One of the important benefits of analyzing sentiment is in appraising the comments that users provide or service providers or services. In this work, a solution known as adaptive rider feedback artificial tree optimization-based deep neuro-fuzzy network (RFATO-based DNFN) is implemented for efficient sentiment grade classification. Here, the input is pre-processed by employing the process of stemming and stop word removal. Then, important factors, e.g. SentiWordNet-based features, such as the mean value, variance, as well as kurtosis, spam word-based features, term frequency-inverse document frequency (TF-IDF) features and emoticon-based features, are extracted. In addition, angular similarity and the decision tree model are employed for grouping the reviewed data into specific sets. Next, the deep neuro-fuzzy network (DNFN) classifier is used to classify the sentiment grade. The proposed adaptive rider feedback artificial tree optimization (A-RFATO) approach is utilized for the training of DNFN. The A-RFATO technique is a combination of the feedback artificial tree (FAT) approach and the rider optimization algorithm (ROA) with an adaptive concept. The effectiveness of the proposed A-RFATO-based DNFN model is evaluated based on such metrics as sensitivity, accuracy, specificity, and precision. The sentiment grade classification method developed achieves better sensitivity, accuracy, specificity, and precision rates when compared with existing approaches based on Large Movie Review Dataset, Datafiniti Product Database, and Amazon reviews.

Źródło:

Journal of Telecommunications and Information Technology; 2023, 1; 37--50
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 25.

Tytuł:

Synthesis and optimization of sequencing operation algorithm

Autorzy:

Ovsyak, O.
Petrushka, J.
Kozelko, M.

Powiązania:

https://bibliotekanauki.pl/articles/114365.pdf

Data publikacji:

2015

Wydawca:

Stowarzyszenie Inżynierów i Techników Mechaników Polskich

Tematy:

algebra of algorithms
operation of sequencing
synthesis of algorithm formula
optimization of algorithm formula

Opis:

Synthesis and optimization ways of sequencing operation applied in computer system, are described in the paper. The ways are general, and use sequencing and eliminating operations of algorithm algebra. They allow for automated synthesis of the sequencing operations. Optimization of algorithm formulas has been made on the basis of the properties of sequencing operations.

Źródło:

Measurement Automation Monitoring; 2015, 61, 10; 484-487
2450-2855

Pojawia się w:

Measurement Automation Monitoring

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 26.

Tytuł:

Modelling of Curvature of the Railway Track Geometrical Layout Using Particle Swarm Optimization

Autorzy:

Palikowska, Katarzyna Małgorzata

Powiązania:

https://bibliotekanauki.pl/articles/504485.pdf

Data publikacji:

2014

Wydawca:

Międzynarodowa Wyższa Szkoła Logistyki i Transportu

Tematy:

Particle Swarm Optimization algorithm cubic C-Bezier curve
curvature of the railway track layout dynamic interactions
transition curve

Opis:

A method of railway track geometrical layout design, based on an application of cubic C-Bezier curves for describing the layout curvature is presented in the article. The control points of a cubic C-Bezier curve are obtained in an optimization process carried out using Particle Swarm Optimization algorithm. The optimization criteria are based on the evaluation of the dynamic interactions and satisfaction of geometrical design requirements.

Źródło:

Logistics and Transport; 2014, 21, 1; 73-82
1734-2015

Pojawia się w:

Logistics and Transport

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 27.

Tytuł:

Tools for optimizing performance of VOYages at sea

Autorzy:

Johannessen, J. A.
Perrin, A.
Gaultier, L.
Herlédan, S.
Pouplin, C.
Collard, F.
Maze, J. P.
Dussauze, M.
Rapp, J.
Fanebust, R.
Andersen, S.
Franks, O.
Meyer, R.

Powiązania:

https://bibliotekanauki.pl/articles/1841544.pdf

Data publikacji:

2021

Wydawca:

Uniwersytet Morski w Gdyni. Wydział Nawigacyjny

Tematy:

voyage at sea
Copernicus Marine Environment Monitoring Service
optimization tool
synthetic aperture radar
finite-size lyapunov exponent
route optimization
sea surface temperature
route optimization algorithm

Opis:

The aim of the TOPVOYS project supported by the MarTERA ERA-Net Cofund program within the European Commission is to advance and implement analyses tools and decision support system for voyage optimisation. Based on marine weather analyses and forecasts combined with near real time satellite-based observations of wind, wave and surface current conditions as well as sea surface temperature fields the best shipping route are examined. The proposed approach aims to identify the optimum balance between minimisation of transit time and fuel consumption as well as reduction of emissions without placing the vessel at risk to damage and or crew injury. As such it is compliant with the International Maritime Organization guidelines [6] for ship routeing to keep the traffic smooth and avoid accidents, notably in the presence of unfavorable marine meteorological conditions. The tool performances will be demonstrated both in post-voyage analyses and real time operations for the North Atlantic Ocean crossings, voyages from Europe through the Mediterranean Sea and the Suez Channel to the Far East (e.g. China, South Korea) and voyages around Southern Africa.

Źródło:

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2021, 15, 1; 233-239
2083-6473
2083-6481

Pojawia się w:

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 28.

Tytuł:

Combined modelling for iron ore demand forecasting with intelligent optimization algorithms
Modelowanie do prognozowania popytu na rudę żelaza połączone z inteligentnymi algorytmami optymalizacji

Autorzy:

Ren, Min
Dai, Jianyong
Zhu, Wancheng
Dai, Feng

Powiązania:

https://bibliotekanauki.pl/articles/1849620.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN

Tematy:

iron ore demand
combined model
intelligent optimization algorithm
forecasting accuracy
ruda żelaza
model połączony
inteligentny algorytm optymalizacji
dokładność prognozowania

Opis:

The stable supply of iron ore resources is not only related to energy security, but also to a country’s sustainable development. The accurate forecast of iron ore demand is of great significance to the industrialization development of a country and even the world. Researchers have not yet reached a consensus about the methods of forecasting iron ore demand. Combining different algorithms and making full use of the advantages of each algorithm is an effective way to develop a prediction model with high accuracy, reliability and generalization performance. The traditional statistical and econometric techniques of the Holt–Winters (HW) non-seasonal exponential smoothing model and autoregressive integrated moving average (ARIMA) model can capture linear processes in data time series. The machine learning methods of support vector machine (SVM) and extreme learning machine (ELM) have the ability to obtain nonlinear features from data of iron ore demand. The advantages of the HW, ARIMA, SVM, and ELM methods are combined in various degrees by intelligent optimization algorithms, including the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and simulated annealing (SA) algorithm. Then the combined forecast models are constructed. The contrastive results clearly show that how a high forecasting accuracy and an excellent robustness could be achieved by the particle swarm optimization algorithm combined model, it is more suitable for predicting data pertaining to the iron ore demand.
Stabilne dostawy zasobów rudy żelaza związane są nie tylko z bezpieczeństwem energetycznym, ale także ze zrównoważonym rozwojem kraju. Dokładna prognoza zapotrzebowania na rudę żelaza ma ogromne znaczenie dla rozwoju industrializacji kraju, a nawet świata. Naukowcy nie osiągnęli jeszcze konsensusu co do metod prognozowania popytu na rudę żelaza. Łączenie różnych algorytmów i pełne wykorzystanie zalet każdego algorytmu to skuteczny sposób na opracowanie modelu predykcyjnego o wysokiej dokładności i niezawodności. W tej publikacji, model Holta-Wintersa (HW) do wygładzania szeregów czasowych, w których występują wahania przypadkowe, jak również autoregresyjny zintegrowany model średniej ruchomej (ARIMA), a także maszyna wektorów nośnych (SVM) i maszyna do ekstremalnego uczenia się (ELM), zostały połączone w celu uchwycenia różnych relacji i charakterystyk na podstawie danych szeregów czasowych, aby dokładnie przewidzieć zapotrzebowanie na rudę żelaza. Zalety czterech algorytmów są w różnym stopniu łączone przez inteligentne algorytmy optymalizacji, w tym algorytm genetyczny, algorytm optymalizacji roju cząstek oraz algorytm symulowanego wyżarzania. Następnie konstruowane są połączone modele. Kontrastowe wyniki wyraźnie pokazują, w jaki sposób można osiągnąć wysoką dokładność prognozowania i doskonałą solidność za pomocą połączonego modelu algorytmu genetycznego. Model taki jest bardziej odpowiedni do przewidywania danych dotyczących zapotrzebowania na rudę żelaza. Opierając się na prognozowanych wynikach połączonego modelu algorytmu genetycznego, możemy stwierdzić, że oczekuje się, iż krajowy popyt na rudę żelaza będzie w przyszłości wykazywał tendencję rozwojową w postaci trwałego, ale powolnego wzrostu.

Źródło:

Gospodarka Surowcami Mineralnymi; 2021, 37, 1; 21-38
0860-0953

Pojawia się w:

Gospodarka Surowcami Mineralnymi

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 29.

Tytuł:

Topology optimization of trusses using bars exchange method

Autorzy:

Bojczuk, D.
Rębosz-Kurdek, A.

Powiązania:

https://bibliotekanauki.pl/articles/202330.pdf

Data publikacji:

2012

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

trusses
algorithm of optimization
optimal topologies
bars exchange

Opis:

The algorithm of optimization of trusses is presented in the paper, where for topology optimization the bars exchange method is used. In the first case, the problem aimed at cost minimization with a constraint set on global stiffness is formulated. In the second case, the problem of minimizing the cost function subjected to stress and cross-sectional area constraints is discussed and here the multiple-load case is taken into consideration. The conditions for introduction of topology modification and its acceptance are specified. The paper is illustrated with three examples.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 2; 185-189
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 30.

Tytuł:

Combined modelling for iron ore demand forecasting with intelligent optimization algorithms
Modelowanie do prognozowania popytu na rudę żelaza połączone z inteligentnymi algorytmami optymalizacji

Autorzy:

Ren, Min
Dai, Jianyong
Zhu, Wancheng
Dai, Feng

Powiązania:

https://bibliotekanauki.pl/articles/1849613.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN

Tematy:

iron ore demand
combined model
intelligent optimization algorithm
forecasting accuracy
ruda żelaza
model połączony
inteligentny algorytm optymalizacji
dokładność prognozowania

Opis:

The stable supply of iron ore resources is not only related to energy security, but also to a country’s sustainable development. The accurate forecast of iron ore demand is of great significance to the industrialization development of a country and even the world. Researchers have not yet reached a consensus about the methods of forecasting iron ore demand. Combining different algorithms and making full use of the advantages of each algorithm is an effective way to develop a prediction model with high accuracy, reliability and generalization performance. The traditional statistical and econometric techniques of the Holt–Winters (HW) non-seasonal exponential smoothing model and autoregressive integrated moving average (ARIMA) model can capture linear processes in data time series. The machine learning methods of support vector machine (SVM) and extreme learning machine (ELM) have the ability to obtain nonlinear features from data of iron ore demand. The advantages of the HW, ARIMA, SVM, and ELM methods are combined in various degrees by intelligent optimization algorithms, including the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and simulated annealing (SA) algorithm. Then the combined forecast models are constructed. The contrastive results clearly show that how a high forecasting accuracy and an excellent robustness could be achieved by the particle swarm optimization algorithm combined model, it is more suitable for predicting data pertaining to the iron ore demand.
Stabilne dostawy zasobów rudy żelaza związane są nie tylko z bezpieczeństwem energetycznym, ale także ze zrównoważonym rozwojem kraju. Dokładna prognoza zapotrzebowania na rudę żelaza ma ogromne znaczenie dla rozwoju industrializacji kraju, a nawet świata. Naukowcy nie osiągnęli jeszcze konsensusu co do metod prognozowania popytu na rudę żelaza. Łączenie różnych algorytmów i pełne wykorzystanie zalet każdego algorytmu to skuteczny sposób na opracowanie modelu predykcyjnego o wysokiej dokładności i niezawodności. W tej publikacji, model Holta-Wintersa (HW) do wygładzania szeregów czasowych, w których występują wahania przypadkowe, jak również autoregresyjny zintegrowany model średniej ruchomej (ARIMA), a także maszyna wektorów nośnych (SVM) i maszyna do ekstremalnego uczenia się (ELM), zostały połączone w celu uchwycenia różnych relacji i charakterystyk na podstawie danych szeregów czasowych, aby dokładnie przewidzieć zapotrzebowanie na rudę żelaza. Zalety czterech algorytmów są w różnym stopniu łączone przez inteligentne algorytmy optymalizacji, w tym algorytm genetyczny, algorytm optymalizacji roju cząstek oraz algorytm symulowanego wyżarzania. Następnie konstruowane są połączone modele. Kontrastowe wyniki wyraźnie pokazują, w jaki sposób można osiągnąć wysoką dokładność prognozowania i doskonałą solidność za pomocą połączonego modelu algorytmu genetycznego. Model taki jest bardziej odpowiedni do przewidywania danych dotyczących zapotrzebowania na rudę żelaza. Opierając się na prognozowanych wynikach połączonego modelu algorytmu genetycznego, możemy stwierdzić, że oczekuje się, iż krajowy popyt na rudę żelaza będzie w przyszłości wykazywał tendencję rozwojową w postaci trwałego, ale powolnego wzrostu.

Źródło:

Gospodarka Surowcami Mineralnymi; 2021, 37, 1; 21-38
0860-0953

Pojawia się w:

Gospodarka Surowcami Mineralnymi

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 31.

Tytuł:

Optimization of induced voltage on buried pipeline from HV power lines using grasshopper algorithm (GOA)

Autorzy:

Bouallag, Khadidja
Djekidel, Rabah
Bessedik, Sid Ahmed

Powiązania:

https://bibliotekanauki.pl/articles/1840901.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN

Tematy:

buried pipeline
grasshopper optimization algorithm
GOA
HV power lines
AC induced voltage
rurociąg podziemny
linie wysokich napięć
napięcie indukowane

Opis:

The buried metallic pipeline which parallels to the HV power line is subject to induced voltages from the AC currents flowing in the conductors, these voltages can affect the operating personnel, pipeline associated equipment, and the pipeline integrity. This paper analyses the induced voltage and current on the buried pipeline running parallel to HV power lines. It also presents an optimization procedure of different parameters that affect the level of the induced voltage in the pipeline during normal operating conditions. A comparison study between the proposed optimization algorithms (GOA, GE, DE and PSO) is done with a maximization of a given objective function. The simulation results establish that the GOA algorithm provides a faster convergence and better solution than the other optimization algorithms. Thus, the statistical analysis according to Friedman’s rank test confirmed the superiority of this proposed algorithm. Furthermore, the results show that the parameters optimization of the metallic pipeline is an effective approach to provide the best performance for mitigation which is generally sufficient to reduce the induced voltage experienced by the buried metallic pipeline to enforce the safety limit.

Źródło:

Diagnostyka; 2021, 22, 2; 105-115
1641-6414
2449-5220

Pojawia się w:

Diagnostyka

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 32.

Tytuł:

Optimization of Short-Lag Spatial Coherence Imaging Method

Autorzy:

Domaradzki, Jakub
Lewandowski, Marcin
Żołek, Norbert

Powiązania:

https://bibliotekanauki.pl/articles/176815.pdf

Data publikacji:

2019

Wydawca:

Polska Akademia Nauk. Czasopisma i Monografie PAN

Tematy:

short lag spatial coherence
synthetic aperture
algorithm optimization
parallel processing

Opis:

The computing performance optimization of the Short-Lag Spatial Coherence (SLSC) method applied to ultrasound data processing is presented. The method is based on the theory that signals from adjacent receivers are correlated, drawing on a simplified conclusion of the van Cittert-Zernike theorem. It has been proven that it can be successfully used in ultrasound data reconstruction with despeckling. Former works have shown that the SLSC method in its original form has two main drawbacks: time-consuming processing and low contrast in the area near the transceivers. In this study, we introduce a method that allows to overcome both of these drawbacks. The presented approach removes the dependency on distance (the “lag” parameter value) between signals used to calculate correlations. The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms. The modified method proposed here leads to constant complexity, thus execution time is independent of the lag parameter value, instead of the linear complexity. The presented approach increases computation speed over 10 times in comparison to the base SLSC algorithm for a typical lag parameter value. The approach also improves the output image quality in shallow areas and does not decrease quality in deeper areas.

Źródło:

Archives of Acoustics; 2019, 44, 4; 669-679
0137-5075

Pojawia się w:

Archives of Acoustics

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 33.

Tytuł:

Applying Hunger Game Search (HGS) for selecting significant blood indicators for early prediction of ICU COVID-19 severity

Autorzy:

Sayed, Safynaz AbdEl-Fattah
ElKorany, Abeer
Sayed, Sabah

Powiązania:

https://bibliotekanauki.pl/articles/27312915.pdf

Data publikacji:

2023

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

ICU severity prediction
COVID-19
clinical blood tests
Hunger Game search
HGS
optimization algorithm
support vector machine
SVM
feature selection

Opis:

This paper introduces an early prognostic model for attempting to predict the severity of patients for ICU admission and detect the most significant features that affect the prediction process using clinical blood data. The proposed model predicts ICU admission for high-severity patients during the first two hours of hospital admission, which would help assist clinicians in decision-making and enable the efficient use of hospital resources. The Hunger Game search (HGS) meta-heuristic algorithm and a support vector machine (SVM) have been integrated to build the proposed prediction model. Furthermore, these have been used for selecting the most informative features from blood test data. Experiments have shown that using HGS for selecting features with the SVM classifier achieved excellent results as compared with four other meta-heuristic algorithms. The model that used the features that were selected by the HGS algorithm accomplished the topmost results (98.6 and 96.5%) for the best and mean accuracy, respectively, as compared to using all of the features that were selected by other popular optimization algorithms.

Źródło:

Computer Science; 2023, 24 (1); 113--136
1508-2806
2300-7036

Pojawia się w:

Computer Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 34.

Tytuł:

Application of the Harmony Search algorithm in solving the inverse heat conduction problem
Zastosowanie algorytmu "Harmony Search" do rozwiązania odwrotnego zagadnienia przewodnictwa ciepła

Autorzy:

Hetmaniok, E.
Jama, D.
Słota, D.
Zielonka, A.

Powiązania:

https://bibliotekanauki.pl/articles/87282.pdf

Data publikacji:

2011

Wydawca:

Politechnika Śląska. Wydawnictwo Politechniki Śląskiej

Tematy:

algorytm optymalizacyjny
Harmony Search
dźwięk
przewodnictwo cieplne
harmonia
zagadnienie odwrotne
optimization algorithm
harmony search
sound
heat conduction
harmony
inverse problem

Opis:

In this paper the inverse heat conduction problem with boundary condition of the third kind is solved by applying the recently invented Harmony Search algorithm belonging to the group of optimization algorithms inspired by the natural behaviors or processes. In this case the applied algorithm imitates the process of searching for the harmony in jazz music composition.In this paper the inverse heat conduction problem with boundary condition of the third kind is solved by applying the recently invented Harmony Search algorithm belonging to the group of optimization algorithms inspired by the natural behaviors or processes. In this case the applied algorithm imitates the process of searching for the harmony in jazz music composition.
Celem niniejszego artykułu jest rozwiązanie odwrotnego zagadnienia przewodnictwa ciepła z warunkiem brzegowym trzeciego rodza- ju przy użyciu niedawno zaproponowanego algorytmu „Harmony Search” (poszukiwania harmonii). Zastosowany algorytm należy do grupy algoryt- mów optymalizacyjnych inspirowanych zachowaniami bądź procesami za- chodzącymi w rzeczywistym świecie, w szczególności imituje proces poszu- kiwania harmonii dźwięków podczas improwizacji jazzowej.

Źródło:

Zeszyty Naukowe. Matematyka Stosowana / Politechnika Śląska; 2011, 1; 99-108
2084-073X

Pojawia się w:

Zeszyty Naukowe. Matematyka Stosowana / Politechnika Śląska

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 35.

Tytuł:

Hybrid binary whale optimization algorithm based on taper shaped transfer function for software defect prediction
Hybrydowy, binarny algorytm WOA oparty na transmitancji stożkowej do prognozowania defektów oprogramowania

Autorzy:

Alnaish, Zakaria A. Hamed
Hasoon, Safwan O.

Powiązania:

https://bibliotekanauki.pl/articles/27315468.pdf

Data publikacji:

2023

Wydawca:

Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej

Tematy:

feature selection
binary whale optimization algorithm
taper-shaped transfer function
software defect prediction
wybór cech
algorytm optymalizacji binarnej
transmitancja stożkowa
przewidywanie defektów oprogramowania

Opis:

Reliability is one of the key factors used to gauge software quality. Software defect prediction (SDP) is one of the most important factors which affectsmeasuring software's reliability. Additionally, the high dimensionality of the features has a direct effect on the accuracy of SDP models.The objective of this paper is to propose a hybrid binary whale optimization algorithm (BWOA) based on taper-shape transfer functions for solving feature selection problems and dimension reduction with a KNN classifier as a new software defect prediction method. In this paper, the values of a real vector that representsthe individual encoding have been converted to binary vector by using the four types of Taper-shaped transfer functionsto enhance the performance of BWOA to reduce the dimension of the search space. The performance of the suggestedmethod (T-BWOA-KNN)was evaluatedusing eleven standard software defect prediction datasets from the PROMISE and NASA repositories depending on the K-Nearest Neighbor (KNN) classifier. Seven evaluation metrics have been used to assess the effectiveness of the suggested method. The experimental results have shownthat the performanceof T-BWOA-KNNproduced promising results compared to other methods including ten methods from the literature, four typesof T-BWOAwith the KNN classifier. In addition, the obtained results are compared and analyzed with other methods from the literature in termsof the average numberof selected features (SF) and accuracy rate (ACC) using the Kendall W test. In this paper, a new hybrid software defect prediction methodcalledT-BWOA-KNNhas been proposed which is concerned with the feature selection problem. The experimental results have provedthatT-BWOA-KNN produced promising performance compared with other methods for most datasets.
Niezawodność jest jednym z kluczowych czynników stosowanych do oceny jakości oprogramowania.Przewidywanie defektów oprogramowania SDP (ang. Software Defect Prediction) jest jednym z najważniejszych czynników wpływających na pomiar niezawodności oprogramowania. Dodatkowo, wysoka wymiarowość cech ma bezpośredni wpływ na dokładność modeli SDP.Celemartykułu jest zaproponowanie hybrydowego algorytmu optymalizacji BWOA (ang. Binary Whale Optimization Algorithm) w oparciu o transmitancję stożkową do rozwiązywania problemów selekcji cech i redukcji wymiarów za pomocą klasyfikatora KNN jako nowej metody przewidywania defektów oprogramowania.W artykule, wartości wektora rzeczywistego, reprezentującego indywidualne kodowanie zostały przekonwertowane na wektor binarny przy użyciu czterech typów funkcji transferu w kształcie stożka w celu zwiększenia wydajności BWOA i zmniejszenia wymiaru przestrzeni poszukiwań.Wydajność sugerowanej metody (T-BWOA-KNN) oceniano przy użyciu jedenastu standardowych zestawów danych do przewidywania defektów oprogramowania z repozytoriów PROMISE i NASA w zależności od klasyfikatora KNN. Do oceny skuteczności sugerowanej metody wykorzystano siedemwskaźników ewaluacyjnych. Wyniki eksperymentów wykazały, że działanie rozwiązania T-BWOA-KNN pozwoliło uzyskaćobiecujące wyniki w porównaniu z innymi metodami, w tym dziesięcioma metodami na podstawie literatury, czterema typami T-BWOA z klasyfikatorem KNN. Dodatkowo, otrzymane wyniki zostały porównanei przeanalizowane innymi metodami z literatury pod kątem średniej liczby wybranych cech (SF) i współczynnika dokładności (ACC), z wykorzystaniem testu W.Kendalla. W pracy, zaproponowano nową hybrydową metodę przewidywania defektów oprogramowania, nazwaną T-BWOA-KNN, która dotyczy problemu wyboru cech. Wyniki eksperymentów wykazały, że w przypadku większości zbiorów danych T-BWOA-KNN uzyskała obiecującą wydajnośćw porównaniu z innymi metodami.

Źródło:

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2023, 13, 4; 85--92
2083-0157
2391-6761

Pojawia się w:

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 36.

Tytuł:

Predicting and minimizing the blasting cost in limestone mines using a combination of gene expression programming and particle swarm optimization

Autorzy:

Bastami, Reza
Bazzazi, Abbas Aghajani
Shoormasti, Hadi Hamidian
Ahangari, Kaveh

Powiązania:

https://bibliotekanauki.pl/articles/1853861.pdf

Data publikacji:

2020

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

kopalnia wapienia
wybuch detonacyjny
regresja nieliniowa
blasting cost
limestone mine
gene expression programming
non-linear multivariate regression
particle swarm optimization algorithm
environmental impacts

Opis:

Blasting cost prediction and optimization is of great importance and significance to achieve optimal fragmentation through controlling the adverse consequences of the blasting process. By gathering explosive data from six limestone mines in Iran, the present study aimed to develop a model to predict blasting cost, by gene expression programming method. The model presented a higher correlation coefficient (0.933) and a lower root mean square error (1088) comparing to the linear and nonlinear multivariate regression models. Based on the sensitivity analysis, spacing and ANFO value had the most and least impact on blasting cost, respectively. In addition to achieving blasting cost equation, the constraints such as frag-mentation, fly rock, and back break were considered and analyzed by the gene expression programming method for blasting cost optimization. The results showed that the ANFO value was 9634 kg, hole dia-meter 76 mm, hole number 398, hole length 8.8 m, burden 2.8 m, spacing 3.4 m, hardness 3 Mhos, and uniaxial compressive strength 530 kg/cm2 as the blast design parameters, and blasting cost was obtainedas 6072 Rials/ton, by taking into account all the constraints. Compared to the lowest blasting cost among the 146-research data (7157 Rials/ton), this cost led to a 15.2% reduction in the blasting cost and optimal control of the adverse consequences of the blasting process.

Źródło:

Archives of Mining Sciences; 2020, 65, 4; 835-850
0860-7001

Pojawia się w:

Archives of Mining Sciences

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 37.

Tytuł:

Optimal tuning procedure for FOPID controller of integrated industrial processes with deadtime

Autorzy:

Anuja, R.
Sivarani, T.S.
Germin Nisha, M.

Powiązania:

https://bibliotekanauki.pl/articles/2173529.pdf

Data publikacji:

2022

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

industrial process integrated with dead time
tuning of FOPID
whale optimization algorithm
proces przemysłowy zintegrowany z czasem martwym
strojenie FOPID
algorytm optymalizacji wielorybów

Opis:

Industrial processes such as batch distillation columns, supply chain, level control etc. integrate dead times in the wake of the transportation times associated with energy, mass and information. The dead time, the cause for the rise in loop variability, also results from the process time and accumulation of time lags. These delays make the system control poor in its asymptotic stability, i.e. its lack of self-regulating savvy. The haste of the controller’s reaction to disturbances and congruence with the design specifications are largely influenced by the dead time; hence it exhorts a heed. This article is aimed at answering the following question: “How can a fractional order proportional integral derivative controller (FOPIDC) be tuned to become a perfect dead time compensator apposite to the dead time integrated industrial process?” The traditional feedback controllers and their tuning methods do not offer adequate resiliency for the controller to combat out the dead time. The whale optimization algorithm (WOA), which is a nascent (2016 developed) swarm-based meta-heuristic algorithm impersonating the hunting maneuver of a humpback whale, is employed in this paper for tuning the FOPIDC. A comprehensive study is performed and the design is corroborated in the MATLAB/Simulink platform using the FOMCON toolbox. The triumph of the WOA tuning is demonstrated through the critical result comparison of WOA tuning with Bat and particle swarm optimization (PSO) algorithm-based tuning methods. Bode plot based stability analysis and the time domain specification based transient analysis are the main study methodologies used.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e139954, 1--8
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 38.

Tytuł:

Aspect-based sentiment classification model employing whale-optimized adaptive neural network

Autorzy:

Balaganesh, Nallathambi
Muneeswaran, K.

Powiązania:

https://bibliotekanauki.pl/articles/2173622.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

aspect-based sentiment analysis
whale optimization algorithm
artificial neural network
opinion mining
analiza nastrojów oparta na aspektach
algorytm optymalizacji wielorybów
sztuczna sieć neuronowa
eksploracja opinii

Opis:

Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence, the enhancement of sentiment classification considering every aspect of products and services is in the limelight. In this proposed research, an aspect-based sentiment classification model has been developed employing sentiment whale-optimized adaptive neural network (SWOANN) for classifying the sentiment for key aspects of products and services. The accuracy of sentiment classification of the product and services has been improved by the optimal selection of weights of neurons in the proposed model. The promising results are obtained by analyzing the mobile phone review dataset when compared with other existing sentiment classification approaches such as support vector machine (SVM) and artificial neural network (ANN). The proposed work uses key features such as the positive opinion score, negative opinion score, and term frequency-inverse document frequency (TF-IDF) for representing each aspect of products and services, which further improves the overall effectiveness of the classifier. The proposed model can be compatible with any sentiment classification problem of products and services.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137271
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 39.

Tytuł:

Aspect-based sentiment classification model employing whale-optimized adaptive neural network

Autorzy:

Balaganesh, Nallathambi
Muneeswaran, K.

Powiązania:

https://bibliotekanauki.pl/articles/2128172.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

aspect-based sentiment analysis
whale optimization algorithm
artificial neural network
opinion mining
analiza nastrojów oparta na aspektach
algorytm optymalizacji wielorybów
sztuczna sieć neuronowa
eksploracja opinii

Opis:

Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence, the enhancement of sentiment classification considering every aspect of products and services is in the limelight. In this proposed research, an aspect-based sentiment classification model has been developed employing sentiment whale-optimized adaptive neural network (SWOANN) for classifying the sentiment for key aspects of products and services. The accuracy of sentiment classification of the product and services has been improved by the optimal selection of weights of neurons in the proposed model. The promising results are obtained by analyzing the mobile phone review dataset when compared with other existing sentiment classification approaches such as support vector machine (SVM) and artificial neural network (ANN). The proposed work uses key features such as the positive opinion score, negative opinion score, and term frequency-inverse document frequency (TF-IDF) for representing each aspect of products and services, which further improves the overall effectiveness of the classifier. The proposed model can be compatible with any sentiment classification problem of products and services.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137271, 1--8
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 40.

Tytuł:

A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO

Autorzy:

Nagaraj, B.
Vijayakumar, P.

Powiązania:

https://bibliotekanauki.pl/articles/384767.pdf

Data publikacji:

2011

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

ant colony algorithm
evolutionary program
genetic algorithm particle swarm optimization and soft computing

Opis:

Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 2; 42-48
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 41.

Tytuł:

Lung cancer detection using an integration of fuzzy K-Means clustering and deep learning techniques for CT lung images

Autorzy:

Prasad, J. Maruthi Nagendra
Chakravarty, S.
Krishna, M. Vamsi

Powiązania:

https://bibliotekanauki.pl/articles/2173683.pdf

Data publikacji:

2022

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

fuzzy K-means
artificial neural networks
SVM
support vector machine
crow search optimization algorithm
algorytm rozmytych k-średnich
sztuczne sieci neuronowe
maszyna wektorów wspierających
algorytm optymalizacji wyszukiwania kruków

Opis:

Computer aided detection systems are used for the provision of second opinion during lung cancer diagnosis. For early-stage detection and treatment false positive reduction stage also plays a vital role. The main motive of this research is to propose a method for lung cancer segmentation. In recent years, lung cancer detection and segmentation of tumors is considered one of the most important steps in the surgical planning and medication preparations. It is very difficult for the researchers to detect the tumor area from the CT (computed tomography) images. The proposed system segments lungs and classify the images into normal and abnormal and consists of two phases, The first phase will be made up of various stages like pre-processing, feature extraction, feature selection, classification and finally, segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care of and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of crow search optimization algorithm, later artificial neural network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the fuzzy K-means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. The proposed system delivers accuracy of 96%, 100% specificity and sensitivity of 99% and it reduces false positives. Experimental results shows that the system outperforms many other systems in the literature in terms of sensitivity, specificity, and accuracy. There is a great tradeoff between effectiveness and efficiency and the proposed system also saves computation time. The work shows that the proposed system which is formed by the integration of fuzzy K-means clustering and deep learning technique is simple yet powerful and was effective in reducing false positives and segments tumors and perform classification and delivers better performance when compared to other strategies in the literature, and this system is giving accurate decision when compared to human doctor’s decision.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139006
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 42.

Tytuł:

Speeding-up convolutional neural networks: A survey

Autorzy:

Lebedev, V.
Lempitsky, V.

Powiązania:

https://bibliotekanauki.pl/articles/201708.pdf

Data publikacji:

2018

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

convolutional neural networks
resource-efficient computation
algorithm optimization
splotowe sieci neuronowe
efektywne zasoby obliczeniowe
optymalizacja algorytmu

Opis:

Convolutional neural networks (CNN) have become ubiquitous in computer vision as well as several other domains, but the sheer size of the modern CNNs means that for the majority of practical applications, a significant speed up and compression are often required. Speeding-up CNNs therefore have become a very active area of research with multiple diverse research directions pursued by many groups in academia and industry. In this short survey, we cover several research directions for speeding up CNNs that have become popular recently. Specifically, we cover approaches based on tensor decompositions, weight quantization, weight pruning, and teacher-student approaches. We also review CNN architectures designed for optimal speed and briefly consider automatic architecture search.

Źródło:

Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 6; 799-811
0239-7528

Pojawia się w:

Bulletin of the Polish Academy of Sciences. Technical Sciences

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 43.

Tytuł:

Surrogate synthesis of excitation systems for frame tangential eddy current probes

Autorzy:

Halchenko, Volodymir Yakovych
Trembovetska, Ruslana Volodymyrivna
Tychkov, Volodymir Volodymyrovych

Powiązania:

https://bibliotekanauki.pl/articles/1955174.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

additive neural network regression
eddy current probe
stochastic optimization algorithm
surrogate optimization
uniform eddy current density distribution
velocity effect
addytywna regresja sieci neuronowej
sonda prądów wirowych
algorytm optymalizacji stochastycznej
optymalizacja zastępcza
równomierny rozkład gęstości prądów wirowych
efekt prędkości

Opis:

Existing scientific studies devoted to the design of eddy-current probes with a priori given configuration of the electromagnetic excitation field, which provide a uniform eddy current density distribution, consider a wide class of such, but are limited to the case when the probe is stationary relative to the testing object. Therefore, the actual problem is the synthesis of moving tangential eddy current probes with a frame excitation system that provides a uniform eddy current density distribution in the testing object, the solution of which is proposed in this study. A mathematical method for nonlinear surrogate synthesis of excitation systems for frame moving tangential surface eddy current probes, which implements a uniform eddy current density distribution of the testing zone object, is proposed. A metamodel of the volumetric structure of the excitation system of the frame tangential eddy current probe, applied in the process of surrogate optimal parametric synthesis, has been created. The examples of nonlinear synthesis of excitation systems using modern metaheuristic stochastic algorithms for finding the global extremum are considered. The numerical results of the obtained solutions of the problems are presented. The efficiency of the synthesized structures of excitation systems in comparison with classical analogs is shown on the graphs of the eddy current density distribution on the object surface in the testing zone.

Źródło:

Archives of Electrical Engineering; 2021, 70, 4; 743-757
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 44.

Tytuł:

On Some Aspects of Genetic and Evolutionary Methods for Optimization Purposes

Autorzy:

Woźniak, M.
Połap, D.

Powiązania:

https://bibliotekanauki.pl/articles/227353.pdf

Data publikacji:

2015

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

computational intelligence
genetic algorithm
heuristic algorithm
optimization

Opis:

In this paper, the idea of applying some hybrid genetic algorithms with gradient local search and evolutionary optimization techniques is formulated. For two different test functions the proposed versions of the algorithms have been examined. Research results are presented and discussed to show potential efficiency in optimization purposes.

Źródło:

International Journal of Electronics and Telecommunications; 2015, 61, 1; 7-16
2300-1933

Pojawia się w:

International Journal of Electronics and Telecommunications

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 45.

Tytuł:

Structural weight minimization of high speed vehicle-passenger catamaran by genetic algorithm

Autorzy:

Sekulski, Z.

Powiązania:

https://bibliotekanauki.pl/articles/258678.pdf

Data publikacji:

2009

Wydawca:

Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa

Tematy:

ship structure
optimization
topology optimization
sizing optimization
genetic algorithm

Opis:

Reduction of hull structural weight is the most important aim in the design of many ship types. But the ability of designers to produce optimal designs of ship structures is severely limited by the calculation techniques available for this task. Complete definition of the optimal structural design requires formulation of size-topology-shape-material optimization task unifying optimization problems from four areas and effective solution of the problem. So far a significant progress towards solution of this problem has not been achieved. In other hand in recent years attempts have been made to apply genetic algorithm (GA) optimization techniques to design of ship structures. An objective of the paper was to create a computer code and investigate a possibility of simultaneous optimization of both topology and scantlings of structural elements of large spacial sections of ships using GA. In the paper GA is applied to solve the problem of structural weight minimisation of a high speed vehicle-passenger catamaran with several design variables as dimensions of the plate thickness, longitudinal stiffeners and transverse frames and spacing between longitudinals and transversal members. Results of numerical experiments obtained using the code are presented. They shows that GA can be an efficient optimization tool for simultaneous design of topology and sizing high speed craft structures.

Źródło:

Polish Maritime Research; 2009, 2; 11-23
1233-2585

Pojawia się w:

Polish Maritime Research

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 46.

Tytuł:

Multi-variable optimization of an ytterbium-doped fiber laser using genetic algorithm

Autorzy:

Hashemi, S. S.
Ghavami, S. S.
Khorsandi, A

Powiązania:

https://bibliotekanauki.pl/articles/175086.pdf

Data publikacji:

2015

Wydawca:

Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej

Tematy:

fiber laser
optimization
genetic algorithm

Opis:

We introduce the genetic algorithm for the optimization of an Yb3+-doped double-clad fiber laser based on a multi-variable scheme. The output characteristic of the laser is numerically simulated using real practical values. This is performed through solving the associated steady-state rate equation and investigating the effects of input variables such as pump and signal wavelengths and length of the fiber on the laser output. It is found that pumping of the medium around 975 nm is conducted to attain the maximum output power of ~34.8 W, while the stability of the outcoupled power is significantly improved when pumping at 920 nm, confirming good agreement with the reported experimental results. We have also found that by using genetic algorithm base multi-variable optimization, the output power can be significantly increased by about three orders of magnitude and reaches to ~28.5 W with optimum and shorter fiber length of ~57.5 m. Obtained results show that based on the genetic algorithm multi-variable discipline, fiber characteristics can be optimized according to the gaining of maximum output power.

Źródło:

Optica Applicata; 2015, 45, 3; 355-367
0078-5466
1899-7015

Pojawia się w:

Optica Applicata

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 47.

Tytuł:

Some Aspects of the Application of Genetic Algorithm for Solving the Assignment Problem of Tasks to Resources in a Transport Company

Autorzy:

Izdebski, Mariusz
Jacyna, Marianna

Powiązania:

https://bibliotekanauki.pl/articles/504281.pdf

Data publikacji:

2014

Wydawca:

Międzynarodowa Wyższa Szkoła Logistyki i Transportu

Tematy:

assignment problem
genetic algorithm
optimization

Opis:

The article defines the assignment problem of tasks to resources in a transport company. The paper describes mathematical model of a transport system taking into account the assignment of vehicles to the tasks. It also provides stages of creation of the genetic algorithm for solving the assignment problem in the transport company.

Źródło:

Logistics and Transport; 2014, 21, 1; 13-20
1734-2015

Pojawia się w:

Logistics and Transport

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 48.

Tytuł:

Ant algorithm for AP-N aimed at optimization of complex systems

Autorzy:

Mikulik, J.
Zajdel, M.

Powiązania:

https://bibliotekanauki.pl/articles/375987.pdf

Data publikacji:

2010

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

assignment problem
ant algorithm
optimization

Opis:

Assignment Problem (AP), which is well known combinatorial problem, has been studied extensively in the course of many operational and technical researches. It has been shown to be NP-hard for three or more dimensions and a few non-deterministic methods have been proposed to solve it. This paper pays attention on new heuristic search method for the n-dimensional assignment problem, based on swarm intelligence and comparing results with those obtained by other scientists. It indicates possible direction of solutions of problems and presents a way of behaviour using ant algorithm for multidimensional optimization complex systems. Results of researches in the form of computational simulations outcomes are presented.

Źródło:

Decision Making in Manufacturing and Services; 2010, 4, 1-2; 29-36
1896-8325
2300-7087

Pojawia się w:

Decision Making in Manufacturing and Services

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 49.

Tytuł:

Optimization of the pulse transformer using circuit-field model

Autorzy:

Łyskawiński, W.
Knypiński, Ł.
Nowak, L.
Jędryczka, C.

Powiązania:

https://bibliotekanauki.pl/articles/1395761.pdf

Data publikacji:

2013

Wydawca:

Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej

Tematy:

pulse transformer
optimization
genetic algorithm

Opis:

The paper presents the new strategy of the optimization of pulse transformer (PT). In order to reduce calculation time the optimization problem has been decomposed into two stages. In the first stage, to determine functional parameters of PT the circuit model is used. The goal of circuit calculations is to limit the space of design variables that meets formulated requirements. The genetic algorithm has been applied for this task. In order to include constraints, the penalty function has been engaged. The transformer dimensions obtained in the first stage of calculations are used as initial values in the second stage of design process. In the second stage the field model of PT is employed. Obtained results prove that presented approach allows for fast optimization of the PT design.

Źródło:

Computer Applications in Electrical Engineering; 2013, 11; 159-167
1508-4248

Pojawia się w:

Computer Applications in Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 50.

Tytuł:

Algorithmic optimization of the calculation with the consideration of the interconnection of the basic economic parameters of the flight route of the model air carrier

Autorzy:

Szabo, Stanislav
Blistanova, Monika
Mako, Sebastian
Vajdova, Iveta
Pilat, Marek

Powiązania:

https://bibliotekanauki.pl/articles/410102.pdf

Data publikacji:

2020

Wydawca:

STE GROUP

Tematy:

algorithm
optimization
economic analysis
load factor

Opis:

The load factor is the determining factor for airlines in economic terms and the prediction of the future development of the flight route. The combination of load factor and break-even point provides the airline with a comprehensive picture of the business of the flight route and the optimization of pricing for the flight route. The purpose of the article is to propose and adapt the development of air transport prices on a given line using maximally recalculated values and maximize profit. The optimized calculation algorithm then facilitates the understanding of the individual steps of the load factor calculation and the monitoring of price development by means of the chi-square mathematical method by which we observed the interconnection of the ticket price and the load factor. To describe the problem, we chose the Bratislava – Larnaca route.

Źródło:

Management Systems in Production Engineering; 2020, 1 (28); 34-39
2299-0461

Pojawia się w:

Management Systems in Production Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 51.

Tytuł:

Optimization of dental implant using genetic algorithm
Optymalizacja wszczepu stomatologicznego z wykorzystaniem algorytmu genetycznego

Autorzy:

Łodygowski, T.
Szajek, K.
Wierszycki, M.

Powiązania:

https://bibliotekanauki.pl/articles/279418.pdf

Data publikacji:

2009

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

design optimization
genetic algorithm
dental implant

Opis:

The subject of the present work is optimization of the modern implant system Osteoplant, which was created and is still developed by Foundation of University of Medical Sciences in Poznań. Clinical observations point to the occurrence of both early and late complications in the case of all two-component implant systems. In many cases, these problems are caused by mechanical fractures of the implants themselves. The obtained results of the previous studies focused on necessary changes of the implant mechanical behavior, which helped to achieve the required long-term strength. However, modifications of the present dental implant system are not obvious. In this paper, an optimization of the Osteoplant dental implant system, with the use of FEA and genetic algorithms is discussed.
Przedmiotem prezentowanej pracy jest problem optymalizacji systemu implantologicznego Osteoplant, który został opracowany i wciąż jest ulepszany przez Fundację Uniwersytetu Medycznego w Poznaniu. Obserwacje kliniczne potwierdzają występowanie powikłań zarówno we wczesnej, jak i późnej fazie użytkowania implantu. Dotychczas otrzymane wyniki wskazują, że wydłużenie bezawaryjnego okresu użytkowania implantu wymaga wprowadzenia zmian w jego pracy mechanicznej. Jednakże, ustalenie szczegłów modyfikacji nie jest oczywiste. W artykule została opisana procedura optymalizacji systemu implantologicznego Osteoplant z użyciem analizy metodą elementów skończonych oraz algorytmu genetycznego.

Źródło:

Journal of Theoretical and Applied Mechanics; 2009, 47, 3; 573-598
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 52.

Tytuł:

Advanced cascaded scheduling for highly autonomous production cells with material flow and tool lifetime consideration using AGVs

Autorzy:

Miller, Eddi
Engelmann, Bastian
Kaupp, Tobias
Schmitt, Jan

Powiązania:

https://bibliotekanauki.pl/articles/24084716.pdf

Data publikacji:

2023

Wydawca:

Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych

Tematy:

scheduling
robotic cell
algorithm
makespan optimization

Opis:

In today’s manufacturing systems, especially in Industry 4.0, highly autonomous production cells play an important role. To reach this goal of autonomy, different technologies like industrial robots, machine tools, and automated guided vehicles (AGV) are deployed simultaneously which creates numerous challenges on various automation levels. One of those challenges regards the scheduling of all applied resources and their corresponding tasks. Combining data from a real production environment and Constraint Programming (CP-SAT), we provide a cascaded scheduling approach that plans production orders for machine tools to minimize makespan and tool changeover time while enabling the corresponding robot for robot-collaborated processes. Simultaneously, AGVs provide all production cells with the necessary material and tools. Hereby, magazine capacity for raw material as well as finished parts and tool service life are taken into account.

Źródło:

Journal of Machine Engineering; 2023, 23, 3; 69--85
1895-7595
2391-8071

Pojawia się w:

Journal of Machine Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 53.

Tytuł:

Performance investigation and element optimization of 2D array transducer using Bat Algorithm

Autorzy:

Tantawy, Dina Mohamed
Eladawy, Mohamed
Hassan, Mohamed Alimaher
Mubarak, Roaa

Powiązania:

https://bibliotekanauki.pl/articles/140685.pdf

Data publikacji:

2020

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

2D ultrasound arrays
Binary Bat Algorithm
Genetic Algorithm
Optimization

Opis:

One of the least expensive and safest diagnostic modalities routinely used is ultrasound imaging. An attractive development in this field is a two-dimensional (2D) matrix probe with three-dimensional (3D) imaging. The main problems to implement this probe come from a large number of elements they need to use. When the number of elements is reduced the side lobes arising from the transducer change along with the grating lobes that are linked to the periodic disposition of the elements. The grating lobes are reduced by placing the elements without any consideration of the grid. In this study, the Binary Bat Algorithm (BBA) is used to optimize the number of active elements in order to lower the side lobe level. The results are compared to other optimization methods to validate the proposed algorithm.

Źródło:

Archives of Electrical Engineering; 2020, 69, 3; 561-579
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 54.

Tytuł:

Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Computational simulations

Autorzy:

Sekulski, Z.

Powiązania:

https://bibliotekanauki.pl/articles/260598.pdf

Data publikacji:

2011

Wydawca:

Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa

Tematy:

ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination

Opis:

Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems of the four areas and giving an effective solution of the problem. So far, a significant progress towards the solution of the problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure, with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members, taken into account. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed by using selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm, are presented. They show that the proposed genetic algorithm can be an efficient tool for multi-objective optimization of ship structures. The paper is published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.

Źródło:

Polish Maritime Research; 2011, 3; 3-30
1233-2585

Pojawia się w:

Polish Maritime Research

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 55.

Tytuł:

Handling insensitivity in multi-physics inverse problems using a complex evolutionary strategy
Rozpoznawanie niewrażliwości w wielokryterialnych problemach odwrotnych przy użyciu złożonej strategii ewolucyjnej

Autorzy:

Sawicki, Jakub
Smołka, Maciej
Łoś, Marcin
Schaefer, Robert

Powiązania:

https://bibliotekanauki.pl/articles/29520322.pdf

Data publikacji:

2019

Wydawca:

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH

Tematy:

multi-objective optimization
evolutionary algorithm
inverse problem

Opis:

In this paper we present a complex strategy for the solution of ill posed, in-verse problems formulated as multiobjective global optimization ones. The strategy is capable of identifying the shape of objective insensitivity regions around connected components of Pareto set. The goal is reached in two phases. In the first, global one, the connected components of the Pareto set are localized and separated in course of the multi-deme, hierarchic memetic strategy HMS. In the second, local phase, the random sample uniformly spread over each Pareto component and its close neighborhood is obtained in the specially profiled evolutionary process using multiwinner selection. Finally, each local sample forms a base for the local approximation of a dominance function. Insensitivity region surrounding each connected component of the Pareto set is estimated by a sufficiently low level set of this approximation. Capabilities of the whole procedure was verified using specially-designed two-criterion benchmarks.
Artykuł prezentuje złożoną strategię rozwiązywania źle postawionych problemów odwrotnych sformułowanych jako wielokryterialne zadania optymalizacji globalnej. Opisana strategia umożliwia identyfikację obszarów niewrażliwości funkcji celu wokół spójnych składowych zbioru Pareto. Cel jest osiągany w dwu etapach. W pierwszym z nich — globalnym — składowe spójne zbioru Pareto są lokalizowane i separowane przy pomocy wielopopulacyjnej hierarchicznej strategii memetycznej HMS. W etapie drugim — lokalnym — przy użyciu specjalnie sprofilowanego procesu ewolucyjnego wykorzystującego operator selekcji wyborczej z wieloma zwycięzcami produkowana jest losowa próbka rozłożona jednostajnie na każdej składowej i jej bliskim otoczeniu. Finalnie każda lokalna próbka jest użyta jako baza do zbudowania lokalnej aproksymacji funkcji dominacji. Zbiory poziomicowe tej aproksymacji dla odpowiednio niskich poziomów stanowią przybliżenie zbiorów niewrażliwości wokół składowych spójnych. Możliwości strategii zostały zweryfikowane przy użyciu specjalnie zaprojektowanych dwukryterialnych funkcji testowych.

Źródło:

Computer Methods in Materials Science; 2019, 19, 1; 2-11
2720-4081
2720-3948

Pojawia się w:

Computer Methods in Materials Science

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 56.

Tytuł:

Passive loop coordinates optimization for mitigation of magnetic field value in the proximity of a power line

Autorzy:

Książkiewicz, M.

Powiązania:

https://bibliotekanauki.pl/articles/97704.pdf

Data publikacji:

2015

Wydawca:

Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej

Tematy:

power line
magnetic field
optimization
genetic algorithm

Opis:

The paper relates to the distribution of the magnetic field generated by the overhead power line, and it’s reduction in the area of interest using a conductive loop placed in the space near the line. The paper presents results obtained from an original program written in C ++, which implements the procedure for calculating the magnetic field generated by overhead line and a genetic algorithm used to optimize the location and loop compensation factor. Examples of the program are presented for horizontal single-track line and three different shielding loop configurations. The first relates to a single loop (4 to 5 parameters to optimize - 4 position coordinates (y, z) and the compensation factor), the second case involves two loops with one common conductor (6 to 8 parameters - 6 coordinates (y, z) and 0 to 2 compensation factors), the third case concerns two independent loops (8 to 10 parameters - 8 coordinates (y, z) and 0 to 2 of the compensation factors). In addition similar calculations are performed for single-track line with two earth wires.

Źródło:

Computer Applications in Electrical Engineering; 2015, 13; 77-87
1508-4248

Pojawia się w:

Computer Applications in Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 57.

Tytuł:

Tuning of a Fuzzy System for Controlling Searching Process In Multi Objective Scheduling Immune Algorithm

Autorzy:

Wosik, I.
Skołud, B.

Powiązania:

https://bibliotekanauki.pl/articles/971215.pdf

Data publikacji:

2009

Wydawca:

Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych

Tematy:

Immune Algorithm
multi objective optimization
fuzzy system

Opis:

In the paper the Multi Objective Immune Algorithm (MOIA) for an open job shop scheduling problem (OJSP) is proposed. The OJSP belongs to most both time consuming and most complicated problems in scope of searching space. In the paper schedules are evaluated by using three criteria: makespan, flowtime and total tardiness. MOIA proposes a schedule, which is best one, selected from a set of achieved solutions. An affinity threshold is a parameter that controls equilibrium between searching space and solutions diversity in MOIA. The affinity threshold is defined by using fuzzy logic system. In the paper fuzzy system is tuned by selecting shape, size of fuzzy sets, and fuzzy decisions of an affinity threshold. If the fuzzy system is used then neither the knowledge about the affinity threshold nor influence over searching processes is not required from a decision-maker. The application of the fuzzy system makes the process of decision-making user friendly. In the paper efficiency of MOIA before and after the fuzzy system tuning is compared and computational results are presented.

Źródło:

Journal of Machine Engineering; 2009, 9, 1; 130-143
1895-7595
2391-8071

Pojawia się w:

Journal of Machine Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 58.

Tytuł:

Optimizing the number of docks at transhipment terminals using genetic algorithm

Autorzy:

Izdebski, M.
Jacyna-Gołda, I.

Powiązania:

https://bibliotekanauki.pl/articles/242009.pdf

Data publikacji:

2017

Wydawca:

Instytut Techniczny Wojsk Lotniczych

Tematy:

transhipment terminal
genetic algorithm
optimization
cross docking

Opis:

This article presents the issue of designating the number of docks at the transhipment terminals using genetic algorithm. Transhipment terminals refer to cross-docking terminals. The main factor that influences on the number of these docks is the stream of cargo flowing into the given terminal. In order to determine this flow of cargo the mathematical model of the distribution of this flow was developed. This model takes into account constraints like those that e.g. processing capacity at the transhipment terminal cannot be exceeded or demand of recipients must be met. The criterion function in this model determines the minimum cost of the flow of cargo between all objects in the transport network. To designate the optimal stream of cargo flowing into the transport network the genetic algorithm was developed. In this article, the stages of construction of this algorithm were presented. The structure processed by the algorithm, the process of crossover and mutation were described. In the article in order to solve the problem of designating the number of docks at the transhipment terminals the genetic algorithm was developed.

Źródło:

Journal of KONES; 2017, 24, 4; 369-376
1231-4005
2354-0133

Pojawia się w:

Journal of KONES

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 59.

Tytuł:

An Assessment of High-Order-Mode Analysis and Shape Optimization of Expansion Chamber Mufflers

Autorzy:

Chiu, M. C.
Chang, Y. C.

Powiązania:

https://bibliotekanauki.pl/articles/178079.pdf

Data publikacji:

2014

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

higher order wave
eigenfunction
optimization
genetic algorithm

Opis:

A substantial quantity of research on muffler design has been restricted to a low frequency range using the plane wave theory. Based on this theory, which is a one-dimensional wave, no higher order wave has been considered. This has resulted in underestimating acoustical performances at higher frequencies when doing muffler analysis via the plane wave model. To overcome the above drawbacks, researchers have assessed a three-dimensional wave propagating for a simple expansion chamber muffler. Therefore, the acoustic effect of a higher order wave (a high frequency wave) is considered here. Unfortunately, there has been scant research on expansion chamber mufflers equipped with baffle plates that enhance noise elimination using a higher-order-mode analysis. Also, space-constrained conditions of industrial muffler designs have never been properly addressed. So, in order to improve the acoustical performance of an expansion chamber muffler within a constrained space, the optimization of an expansion chamber muffler hybridized with multiple baffle plates will be assessed. In this paper, the acoustical model of the expansion chamber muffler will be established by assuming that it is a rigid rectangular tube driven by a piston along the tube wall. Using an eigenfunction (higher- order-mode analysis), a four-pole system matrix for evaluating acoustic performance (STL) is derived. To improve the acoustic performance of the expansion chamber muffler, three kinds of expansion chamber mufflers (KA-KC) with different acoustic mechanisms are introduced and optimized for a targeted tone using a genetic algorithm (GA). Before the optimization process is performed, the higher-order-mode mathematical models of three expansion chamber mufflers (A-C) with various allocations of inlets/outlets and various chambers are also confirmed for accuracy. Results reveal that the STL of the expansion chamber mufflers at the targeted tone has been largely improved and the acoustic performance of a reverse expansion chamber muffler is more efficient than that of a straight expansion chamber muffler. Moreover, the STL of the expansion chamber mufflers will increase as the number of the chambers that separate with baffles increases.

Źródło:

Archives of Acoustics; 2014, 39, 4; 489-499
0137-5075

Pojawia się w:

Archives of Acoustics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 60.

Tytuł:

A new concept of an artificial ecosystem algorithm for optimization problems

Autorzy:

Baczynski, D.

Powiązania:

https://bibliotekanauki.pl/articles/205935.pdf

Data publikacji:

2016

Wydawca:

Polska Akademia Nauk. Instytut Badań Systemowych PAN

Tematy:

artificial ecosystem algorithm
optimization
computational intelligence methods

Opis:

This article provides, first, a review of applications of the ecosystem idea in different computational intelligence methods. The article presents the bases of ecosystem operation and a new concept for modelling the phenomena occurring in an ecosystem, with the aim of using these for optimization purposes. The author’s original form of the Artificial Ecosystem Algorithm (AEA) and its constituent parts are presented. The construction of the proposed algorithm was dedicated for continuous optimisation. The operation of the Artificial Ecosystem Algorithm is also compared with an Evolutionary Algorithm and PSO for six test functions for various numbers of variables. Conclusions concerning operation, structure and complexity of AEA are provided at the end.

Źródło:

Control and Cybernetics; 2016, 45, 1; 5-36
0324-8569

Pojawia się w:

Control and Cybernetics

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 61.

Tytuł:

Network routing method for ships and other moving objects using MATLAB

Autorzy:

Sakharov, Vladimir V.
Chertkov, Alexandr A.
Ariefjew, Igor B.

Powiązania:

https://bibliotekanauki.pl/articles/135140.pdf

Data publikacji:

2020

Wydawca:

Akademia Morska w Szczecinie. Wydawnictwo AMSz

Tematy:

algorithm
path
optimization
transport
automation
moving object

Opis:

Task planning involves automating the creation of the routes for vessels with known coordinates in a confined space. The management of vessel release in a given area affects the time required for a vessel to complete its voyage, and maximizing vessel performance involves identifying the shortest route. A key issue in automating the generation of the optimal (shortest) routes is selecting the appropriate mathematical apparatus. This paper considers an optimization method based on a recursive algorithm using Bellman-Ford routing tasks for large dimensions. Unlike other optimization techniques, the proposed method enables the shortest path to be assessed in a network model with a complex topology, even if there are arcs with negative weights. The practical implementation of the modified Floyd algorithm was demonstrated using a sample automated build and using it to calculate a network model with a complex topology, using an iterative procedure for a program prepared in MATLAB. Implementation of the computer model is simple, and unlike existing models, it eliminates restrictions associated with the presence of negative weights and cycles on a network and automates search shortcuts in ground branch functional means in MATLAB. To confirm the accuracy of the obtained results, we performed an example calculation using the network. The proposed algorithm and recursive procedure are recommended for finding energy-efficient solutions during the management of mobile objects on waterways.

Źródło:

Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2020, 62 (134); 61-68
1733-8670
2392-0378

Pojawia się w:

Zeszyty Naukowe Akademii Morskiej w Szczecinie

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 62.

Tytuł:

Efficiency improvement of switched reluctance generator using optimization techniques

Autorzy:

Reis, M. R. C.
Araújo, W. R. H.
Calixto, W. P.

Powiązania:

https://bibliotekanauki.pl/articles/136169.pdf

Data publikacji:

2017

Wydawca:

EEEIC International Barbara Leonowicz Szabłowska

Tematy:

switched reluctance generator
optimization
control
genetic algorithm

Opis:

This article introduces the switched reluctance machine operating as a generator. This kind of electrical machine delivers CC power at the output and the energy generated can be controlled through several variables. In this work, the switching angles of the machine's power converter are optimized using deterministic and heuristic techniques so that the output power is kept constant via PI controller while guaranteeing maximum value for machine performance, even for different excitation values and mechanical power on the shaft.

Źródło:

Transactions on Environment and Electrical Engineering; 2017, 2, 1; 74-80
2450-5730

Pojawia się w:

Transactions on Environment and Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 63.

Tytuł:

Multiobjective and multiscale optimization of composite materials by means of evolutionary computations

Autorzy:

Beluch, W.
Długosz, A.

Powiązania:

https://bibliotekanauki.pl/articles/280584.pdf

Data publikacji:

2016

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

composite
numerical homogenization
multiobjective optimization
evolutionary algorithm

Opis:

The paper deals with the multiobjective and multiscale optimization of heterogeneous structures by means of computational intelligence methods. The aim of the paper is to find optimal properties of composite structures in a macro scale modifying their microstructure. At least two contradictory optimization criteria are considered simultaneously. A numerical homogenization concept with a representative volume element is applied to obtain equivalent macro-scale elastic constants. An in-house multiobjective evolutionary algorithm MOOPTIM is applied to solve the considered optimization tasks. The finite element method is used to solve the boundary-value problem in both scales. A numerical example is attached.

Źródło:

Journal of Theoretical and Applied Mechanics; 2016, 54, 2; 397-409
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 64.

Tytuł:

Ship Trajectory Control Optimization in Anti-collision Maneuvering

Autorzy:

Zhang, J. F.
Yang, X. D.
Zhang, D.
Haugen, S.

Powiązania:

https://bibliotekanauki.pl/articles/116373.pdf

Data publikacji:

2013

Wydawca:

Uniwersytet Morski w Gdyni. Wydział Nawigacyjny

Tematy:

anticollision
ship trajectory
genetic algorithm
route optimization

Opis:

A lot of attention is being paid to ship’s intelligent anti‐collision by researchers. Several solutions have been introduced to find an optimum trajectory for ship, such as Game Theory, Genetic or Evolutionary Algorithms and so on. However, ship’s maneuverability should be taken into consideration before their real applications. Ship’s trajectory control in anti‐collision maneuvering is studied in this paper. At first, a simple linear ship maneuverability model is introduced to simulate its movement under different speed and rudder angle. After that, ship’s trajectory control is studied by considering the duration of rudder, operation distance to turning points, and maximum angular velocity. The details for algorithm design are also introduced. By giving some restrictions according to the requirements from COLREGs, the intervals for rudder angle in different circumstances can be determined based on the curves. The results can give very meaningful guidance for seafarers when making decisions.

Źródło:

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2013, 7, 1; 89-93
2083-6473
2083-6481

Pojawia się w:

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 65.

Tytuł:

Function optimization using metaheuristics

Autorzy:

Pilski, M.
Seredyński, F.

Powiązania:

https://bibliotekanauki.pl/articles/92887.pdf

Data publikacji:

2006

Wydawca:

Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach

Tematy:

particle swarm optimization (PSO)
artificial immune system
genetic algorithm
function optimization

Opis:

The paper presents the results of comparison of three metaheuristics that currently exist in the problem of function optimization. The first algorithm is Particle Swarm Optimization (PSO) - the algorithm has recently emerged. The next one is based on a paradigm of Artificial Immune System (AIS). Both algorithms are compared with Genetic Algorithm (GA). The algorithms are applied to optimize a set of functions well known in the area of evolutionary computation. Experimental results show that it is difficult to unambiguously select one best algorithm which outperforms other tested metaheuristics.

Źródło:

Studia Informatica : systems and information technology; 2006, 1(7); 77-91
1731-2264

Pojawia się w:

Studia Informatica : systems and information technology

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 66.

Tytuł:

Algorytmy stadne w problemach optymalizacji
Swarm Algorithms in Optimization Problems

Autorzy:

Filipowicz, B.
Kwiecień, J.

Powiązania:

https://bibliotekanauki.pl/articles/274567.pdf

Data publikacji:

2011

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

optymalizacja nieliniowa
algorytm PSO
algorytm pszczeli
algorytm świetlika
nonlinear optimization
particle swarm optimization (PSO)
bee algorithm
firefly algorithm

Opis:

W artykule przedstawiono zastosowanie algorytmu optymalizacji rojem cząstek, algorytmu pszczelego i algorytmu świetlika do wyznaczenia optymalnego rozwiązania wybranych testowych funkcji ciągłych. Przedstawiono i porównano wyniki badań dla funkcji Rosenbrocka, Rastrigina i de Jonga.
This paper presents particle swarm optimization, bee algorithm and firefly algorithm, used for optimal solution of selected continuous well-known functions. Results of these algorithms are compared to each other on Rosenbrock, Rastrigin and de Jong functions.

Źródło:

Pomiary Automatyka Robotyka; 2011, 15, 12; 152-157
1427-9126

Pojawia się w:

Pomiary Automatyka Robotyka

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 67.

Tytuł:

Optimization of electric and magnetic field intensities in proximity of power lines using genetic and particle swarm algorithms

Autorzy:

Król, K.
Machczyński, W.

Powiązania:

https://bibliotekanauki.pl/articles/141588.pdf

Data publikacji:

2018

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

power line
electric field
magnetic field
optimization
genetic algorithm
particle swarm algorithm

Opis:

The paper presents optimization of power line geometrical parameters aimed to reduce the intensity of the electric field and magnetic field intensity under an overhead power line with the use of a genetic algorithm (AG) and particle swarm optimization (PSO). The variation of charge distribution along the conductors as well as the sag of the overhead line and induced currents in earth wires were taken into account. The conductor sag was approximated by a chain curve. The charge simulation method (CSM) and the method of images were used in the simulations of an electric field, while a magnetic field were calculated using the Biot–Savart law. Sample calculations in a three-dimensional system were made for a 220 kV single – circuit power line. A comparison of the used optimization algorithms was made.

Źródło:

Archives of Electrical Engineering; 2018, 67, 4; 829-843
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 68.

Tytuł:

Evolutionary algorithm with a configurable search mechanism

Autorzy:

Łapa, Krystian
Cpałka, Krzysztof
Laskowski, Łukasz
Cader, Andrzej
Zeng, Zhigang

Powiązania:

https://bibliotekanauki.pl/articles/1837536.pdf

Data publikacji:

2020

Wydawca:

Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych

Tematy:

evolutionary algorithm
population-based algorithm
optimization
operator pool
operator selection
individual selection

Opis:

In this paper, we propose a new population-based evolutionary algorithm that automatically configures the used search mechanism during its operation, which consists in choosing for each individual of the population a single evolutionary operator from the pool. The pool of operators comes from various evolutionary algorithms. With this idea, a flexible balance between exploration and exploitation of the problem domain can be achieved. The approach proposed in this paper might offer an inspirational alternative in creating evolutionary algorithms and their modifications. Moreover, different strategies for mutating those parts of individuals that encode the used search operators are also taken into account. The effectiveness of the proposed algorithm has been tested using typical benchmarks used to test evolutionary algorithms.

Źródło:

Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 151-171
2083-2567
2449-6499

Pojawia się w:

Journal of Artificial Intelligence and Soft Computing Research

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 69.

Tytuł:

A New Optimization Algorithm for Dilation and Erosion

Autorzy:

Yin, K.

Powiązania:

https://bibliotekanauki.pl/articles/108794.pdf

Data publikacji:

2011

Wydawca:

Społeczna Akademia Nauk w Łodzi

Tematy:

dilation
erosion
optimization
iteration algorithm
time complexity analysis

Opis:

Effectively optimizing dilation and erosion is an extensively studied but not completely resolved problem. In this paper, a new optimization algorithm is proposed to improve the efficiency of dilation and erosion. Four notions are given to define the edges for any simply connected structuring element (SE). An assistant algorithm is proposed to detect these edges. Based on these notions, three iteration equations can be derived, which redefine dilation and erosion as iteration calculation. Time complexity of the new algorithm is reduced to O(n³). In addition, the new algorithm is suitable for online applications without the decomposition of SE. Simulation shows that with the same parameters, the performance of the new algorithm is better than that of Yang's algorithm.

Źródło:

Journal of Applied Computer Science Methods; 2011, 3 No. 1; 5-16
1689-9636

Pojawia się w:

Journal of Applied Computer Science Methods

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 70.

Tytuł:

Energy absorption by ferromagnetic nanoparticles in hyperthermia therapy

Autorzy:

Kurgan, E.

Powiązania:

https://bibliotekanauki.pl/articles/140857.pdf

Data publikacji:

2012

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

evolutionary algorithm
parametric optimization
DC electric series motor

Opis:

A numerical method is developed for estimation of temperature distributions inside tissues heated by external RF hyperthermia with external circular coil. The computational method relies on a solution of electromagnetic field problem in sinusoidal steadyt state. The heat transfer problem is treated in three dimensions with axis symmetry model. Than the bioheat diffusion equation under a steady-state condition is solved to determine the temperature distributions inside tumour and surrounding tissues. The heat removal due to the blood circulation is also taken into account. Numerical results are presented for heat generated by ferromagnetic nanoparticles in order to minimize negative effects of radiofrequency radiation.

Źródło:

Archives of Electrical Engineering; 2012, 61, 4; 597-608
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 71.

Tytuł:

Evolutionary algorithm for learning Bayesian structures from data

Autorzy:

Kozłowski, M.
Wierzchoń, S. T.

Powiązania:

https://bibliotekanauki.pl/articles/1986916.pdf

Data publikacji:

2002

Wydawca:

Politechnika Gdańska

Tematy:

Bayesian networks
structure learning
evolutionary algorithm
discrete optimization

Opis:

In this paper we report an evolutionary approach to learning Bayesian networks from data. We explain reasons, which advocate such a non-deterministic approach. We analyze weaknesses of previous works and come to conclusion that we should operate in the search space native for the problem i.e. in the space of directed acyclic graphs instead of standard space of binary strings. This requires adaptation of evolutionary methodology into very specific needs. We propose quite new data representation and implementation of generalized genetic operators and then we present an efficient algorithm capable of learning complex networks without additional assumptions. We discuss results obtained with this algorithm. The approach presented in this paper can be extended with the possibility to absorb some suggestions from experts or obtained by means of data preprocessing.

Źródło:

TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2002, 6, 3; 509-521
1428-6394

Pojawia się w:

TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 72.

Tytuł:

Use of computer assistance in order to designate the tasks in the municipal services companies

Autorzy:

Izdebski, M.
Jacyna, M.

Powiązania:

https://bibliotekanauki.pl/articles/241863.pdf

Data publikacji:

2014

Wydawca:

Instytut Techniczny Wojsk Lotniczych

Tematy:

municipal services companies
transport
optimization
genetic algorithm
verification

Opis:

In this article, the method of designating the tasks in the municipal services companies was described. Presented method consists of three phase: the preparatory phase, the optimization phase and the generated tasks phase. Each phase was characterized. In this paper, the mathematical model of this problem was presented. The function of criterion and the condition on designating the tasks were defined. The minimum route described in the optimization phase was designated by the genetic algorithm. In this paper, the stages of constructing of the genetic algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process, the roulette method was used and in the crossover, process the operator PMX was presented. The method was verified in programming language C #. The process of verification was divided into two stages. In the first stage, the best parameters of the genetics algorithm were designated. In the second stage, the algorithm was started with these parameters and the result was compared with the random search algorithm. The random search algorithm generates 2000 routes and the best result is compared with the genetic algorithm. The influence of the inversion, the mutation and the crossover on quality of the results was examined.

Źródło:

Journal of KONES; 2014, 21, 2; 105-112
1231-4005
2354-0133

Pojawia się w:

Journal of KONES

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 73.

Tytuł:

Planning and management of aircraft maintenance using a genetic algorithm

Autorzy:

Kowalski, Mirosław
Izdebski, Mariusz
Żak, Jolanta
Gołda, Paweł
Manerowski, Jerzy

Powiązania:

https://bibliotekanauki.pl/articles/1841765.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN

Tematy:

aircraft operation
maintenance
multi-criteria optimization
genetic algorithm

Opis:

The aim of the article was to develop a tool to support the process of planning and managing aircraft (ac) maintenance. Aircraft maintenance management has been presented for scheduled technical inspections resulting from manufacturers’ technical documentation for ac. The authors defined the problem under investigation in the form of a four-phase decisionmaking process taking into account assignment of aircraft to airports and maintenance stations, assignment of crew to maintenance points, setting the schedules, i.e. working days on which aircraft are directed to maintenance facilities. This approach to the planning and management of aircraft maintenance is a new approach, unprecedented in the literature. The authors have developed a mathematical model for aircraft maintenance planning and management in a multi-criteria approach and an optimisation tool based on the operation of a genetic algorithm. To solve the problem, a genetic algorithm was proposed. The individual steps of the algorithm construction were discussed and its effectiveness was verified using real data.

Źródło:

Eksploatacja i Niezawodność; 2021, 23, 1; 143-153
1507-2711

Pojawia się w:

Eksploatacja i Niezawodność

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 74.

Tytuł:

Optimal distribution of sub-assemblies in stores of factory by evolutionary algorithms
Optymalizacja rozkładu podzespołów w magazynach fabryki przy pomocy algorytmów ewolucyjnych

Autorzy:

Mrówczyńska, B.

Powiązania:

https://bibliotekanauki.pl/articles/328838.pdf

Data publikacji:

2007

Wydawca:

Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN

Tematy:

algorytm ewolucyjny
optymalizacja
magazyn
evolutionary algorithm
optimization
store

Opis:

The paper deals with an application of evolutionary algorithms for optimisation of sub-assemblies distribution in the stores of factory. Numerical model is presented. The fitness function is expressed as a function of distances between stores and assembly rooms and costs of inner transport. Penalty function is used to include restrictions. The results showed that the applied method is the efficient tool for solving such problems.
W artykule przedstawiono zastosowanie algorytmów ewolucyjnych do optymalizacji rozłożenia podzespołów i materiałów wykorzystywanych w produkcji w magazynach zakładu produkcyjnego. Przedstawiono model numeryczny problemu. Funkcję przystosowania wyrażono jako funkcję odległości pomiędzy magazynami a halami montażowymi i kosztów wewnętrznego transportu między nimi. Ograniczenia na pojemność poszczególnych magazynów uwzględniono stosując funkcję kary. Otrzymane wyniki są optymalne i potwierdzają skuteczność algorytmów ewolucyjnych w rozwiązywaniu tego typu problemów.

Źródło:

Diagnostyka; 2007, 4(44); 73-76
1641-6414
2449-5220

Pojawia się w:

Diagnostyka

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 75.

Tytuł:

Flexible job shop problem - parallel tabu search algorithm for multi-GPU

Autorzy:

Bożejko, W.
Uchroński, M.
Wodecki, M.

Powiązania:

https://bibliotekanauki.pl/articles/229502.pdf

Data publikacji:

2012

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

jobs scheduling
flexible manufacturing
parallel algorithm
discrete optimization

Opis:

In the paper we propose a new framework for the distributed tabu search algorithm designed to be executed with the use of a multi-GPU cluster, in which cluster of nodes are equipped with multicore GPU computing units. The proposed methodology is designed specially to solve difficult discrete optimization problems, such as a flexible job shop scheduling problem, which we introduce as a case study used to analyze the efficiency of the designed synchronous algorithm.

Źródło:

Archives of Control Sciences; 2012, 22, 4; 389-397
1230-2384

Pojawia się w:

Archives of Control Sciences

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 76.

Tytuł:

Planning and management of aircraft maintenance using a genetic algorithm

Autorzy:

Kowalski, Mirosław
Izdebski, Mariusz
Żak, Jolanta
Gołda, Paweł
Manerowski, Jerzy

Powiązania:

https://bibliotekanauki.pl/articles/1841824.pdf

Data publikacji:

2021

Wydawca:

Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN

Tematy:

aircraft operation
maintenance
multi-criteria optimization
genetic algorithm

Opis:

The aim of the article was to develop a tool to support the process of planning and managing aircraft (ac) maintenance. Aircraft maintenance management has been presented for scheduled technical inspections resulting from manufacturers’ technical documentation for ac. The authors defined the problem under investigation in the form of a four-phase decisionmaking process taking into account assignment of aircraft to airports and maintenance stations, assignment of crew to maintenance points, setting the schedules, i.e. working days on which aircraft are directed to maintenance facilities. This approach to the planning and management of aircraft maintenance is a new approach, unprecedented in the literature. The authors have developed a mathematical model for aircraft maintenance planning and management in a multi-criteria approach and an optimisation tool based on the operation of a genetic algorithm. To solve the problem, a genetic algorithm was proposed. The individual steps of the algorithm construction were discussed and its effectiveness was verified using real data.

Źródło:

Eksploatacja i Niezawodność; 2021, 23, 1; 143-153
1507-2711

Pojawia się w:

Eksploatacja i Niezawodność

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 77.

Tytuł:

A new nondeterministic method for optimal selection of master degrees of freedom for dynamic condensation based on evolutionary optimization

Autorzy:

Mucha, Waldemar

Powiązania:

https://bibliotekanauki.pl/articles/1839637.pdf

Data publikacji:

2020

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

dynamic condensation
optimization
evolutionary algorithm
model order reduction

Opis:

The following paper presents a new method for choosing a set of master degrees of freedom for the process of dynamic condensation in order to reduce a finite element model. The general rule is that the more degrees of freedom are eliminated, the more accurate the reduced model is. However, eliminating different subsets (of equal sizes) of degrees of freedom may influence the accuracy differently. Therefore, choosing an optimal subset is crucial. The presented method is based on multicriterial evolutionary optimization which makes it the first nondeterministic approach based on computational optimization technique for this application.

Źródło:

Journal of Theoretical and Applied Mechanics; 2020, 58, 2; 445-458
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 78.

Tytuł:

An exact algorithm for design of content delivery networks in MPLS environment

Autorzy:

Walkowiak, K.

Powiązania:

https://bibliotekanauki.pl/articles/308183.pdf

Data publikacji:

2004

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

content delivery network
optimization
branch-and-cut algorithm

Opis:

Content delivery network (CDN) is an efficient and inexpensive method to improve Internet service quality. In this paper we formulate an optimisation problem of replica location in a CDN using MPLS techniques. A novelty, comparing to previous work on this subject, is modelling the network flow as connection-oriented and introduction of capacity constraint on network links to the problem. Since the considered optimisation problem is NP-complete, we propose and discuss exact algorithm based on the branch-and-cut and branch-and-bound methods. We present results of numerical experiments showing comparison of branch-and-cut and branch-and-bound methods.

Źródło:

Journal of Telecommunications and Information Technology; 2004, 2; 13-22
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 79.

Tytuł:

ACO-Inspired Energy-Aware Routing Algorithm for Wireless Sensor Networks

Autorzy:

Yamamoto, Ryo
Nishibu, Seira
Yamazaki, Taku
Okamura, Yasushi
Tanaka, Yoshiaki

Powiązania:

https://bibliotekanauki.pl/articles/308447.pdf

Data publikacji:

2019

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

ant colony optimization
loadbalancing
routing algorithm
sensor networks

Opis:

Multi-hop networks, such as WSNs, become an object of increasing attention as an emerging technology which plays an important role for practical IoT applications. These multi-hop networks generally consist of mobile and small terminals with limited resources, which makes them vulnerable to various network status changes. Moreover, the limited nature of terminal resources available, especially in terms of battery capacity, is one of the most important issues to be addressed in order to prolong their operating time. In order to ensure efficient communications in such networks, much research has already been conducted, especially in the field of routing and transmission technologies. However, conventional approaches adopted in the routing field still suffer from the so-called energy hole problem, usually caused by unbalanced communication loads existing due to difficulties in adaptive route management. To address this issue, the present paper proposes a novel routing algorithm that utilizes ACO-inspired routing based on residual energy of terminals. Operational evaluation reveals its potential to ensure balanced energy consumption and to boost network performance.

Źródło:

Journal of Telecommunications and Information Technology; 2019, 1; 5-13
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 80.

Tytuł:

Recognizing Sets in Evolutionary Multiobjective Optimization

Autorzy:

Gajda-Zagórska, E.

Powiązania:

https://bibliotekanauki.pl/articles/308467.pdf

Data publikacji:

2012

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

basin of attraction
clustering
genetic algorithm
multiobjective optimization

Opis:

Among Evolutionary Multiobjective Optimization Algorithms (EMOA) there are many which find only Paretooptimal solutions. These may not be enough in case of multimodal problems and non-connected Pareto fronts, where more information about the shape of the landscape is required. We propose a Multiobjective Clustered Evolutionary Strategy (MCES) which combines a hierarchic genetic algorithm consisting of multiple populations with EMOA rank selection. In the next stage, the genetic sample is clustered to recognize regions with high density of individuals. These regions are occupied by solutions from the neighborhood of the Pareto set. We discuss genetic algorithms with heuristic and the concept of well-tuning which allows for theoretical verification of the presented strategy. Numerical results begin with one example of clustering in a single-objective benchmark problem. Afterwards, we give an illustration of the EMOA rank selection in a simple two-criteria minimization problem and provide results of the simulation of MCES for multimodal, multi-connected example. The strategy copes with multimodal problems without losing local solutions and gives better insight into the shape of the evolutionary landscape. What is more, the stability of solutions in MCES may be analyzed analytically.

Źródło:

Journal of Telecommunications and Information Technology; 2012, 1; 74-82
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 81.

Tytuł:

Parallel evolutionary algorithms in shape optimization of heat radiators
Zastosowanie równoległego algorytmu ewolucyjnego do optymalizacji kształtu radiatorów

Autorzy:

Burczyński, T.
Długosz, A.
Kuś, W.

Powiązania:

https://bibliotekanauki.pl/articles/280305.pdf

Data publikacji:

2006

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

coupled thermoelasticity
radiation
finite element method
parallel evolutionary algorithm
evolutionary optimization
shape optimization

Opis:

The paper deals with the application of Parallel Evolutionary Algorithms (PEA) and the Finite Element Method (FEM) in shape optimization of heat radiators. The fitness function is computed with the use of the coupled thermoelsticity modelled by MARC/MENTAT software. The geometry, mesh and boundary conditions are created on the basis of a script language implemented in MENTAT. In order to reduce the number of design parameters in evolutionary algorithms, the shape of the structure is modelled by Bezier curves. Numerical examples for some shape optimization are included.
W pracy przedstawiono zastosowanie algorytmów ewolucyjnych oraz metody elementów skończonych (MES) w optymalizacji kształtu radiatorów. Zastosowano algorytm ewolucyjny, w którym funkcja celu wyznaczana jest w sposób równoległy, więc obliczenia przeprowadzane mogą być na wielu komputerach wieloprocesorowych. Tego typu podejście znacznie skraca czas obliczeń w porównaniu do sekwencyjnego algorytmu ewolucyjnego. Wartość funkcji celu wyznaczana jest na podstawie rozwiązania zagadnienia termosprężystości z wykorzystaniem oprogramowania MES MARC/MENTAT. Przy rozwiązywania zagadnienia bezpośredniego uwzględniany jest radiacyjny strumień ciepła. Wyznaczenie stref zacieniania, niezbędnych do jego wyznaczenia, realizowane jest również za pomocą procesora MENTAT. W celu zmniejszenia liczby zmiennych projektowych przy modelowaniu geometrii radiatora wykorzystano krzywe Beziera. Ponadto praca zawiera przykłady numeryczne optymalizacji dla różnych konfiguracji warunków brzegowych.

Źródło:

Journal of Theoretical and Applied Mechanics; 2006, 44, 2; 351-366
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 82.

Tytuł:

A hybrid ant colony for multiresponse mixed-integer problems

Autorzy:

Kushwaha, S.
Mukherjee, I.

Powiązania:

https://bibliotekanauki.pl/articles/409419.pdf

Data publikacji:

2012

Wydawca:

Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej

Tematy:

ant colony optimization(ACO)
desirability functions
genetic algorithm (GA)
multiple response optimization(MRO)

Opis:

In this paper, a hybrid ant colony optimization (ACO) is used to solve a multiple response optimization problem with mixed-integer (MI) search space. The work reported in this paper may be clasified into three part. The first part discusses on relevant litratures and the methodology to solve multiple response optimization problem. The second part provide details on the working principal, parameter tuning of a hybrid ACO proposed for mixed integer state space. In the hybrid ACO, genetic algorithm (GA) is used for intensification of the search strategy. Standard single response (objective) test functions are selected to verify the suitability of hybrid ACO. The third part of this research work illustrates the application of the hybrid ACO in a multiple response optimization (MRO) problem. Statistical experimentation, partial least square regression, 'maximin' desirability function, and hybrid ACO is used to solve the MRO problem. The results confirm the suitability of the hybid ACO for a typical MI MRO problem.

Źródło:

Research in Logistics & Production; 2012, 2, 4; 317-327
2083-4942
2083-4950

Pojawia się w:

Research in Logistics & Production

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 83.

Tytuł:

Multi-objective design optimization of five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet machine

Autorzy:

Nekoubin, Amir
Soltani, Jafar
Dowlatshah, Milad

Powiązania:

https://bibliotekanauki.pl/articles/949883.pdf

Data publikacji:

2020

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

Finite Element Method
genetic algorithm
optimization
permanent-magnet motors

Opis:

The multi-phase permanent-magnet machines with a fractional-slot concentratedwinding (FSCW) are a suitable choice for certain purposes like aircraft, marine, and electric vehicles, because of the fault tolerance and high power density capability. The paper aims to design, optimize and prototype a five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet motor. To optimize the designed multi-phase motor a multi-objective optimization technique based on the genetic algorithm method is applied. The machine design objectives are to maximize torque density of the motor and maximize efficiency then to determine the best choice of the designed machine parameters. Then, the two-dimensional Finite Element Method (2D-FEM) is employed to verify the performance of the optimized machine. Finally, the optimized machine is prototyped. The paper found that the results of the prototyped machine validate the results of theatrical analyses of the machine and accurate consideration of the parameters improved the acting of the machine.

Źródło:

Archives of Electrical Engineering; 2020, 69, 4; 873-889
1427-4221
2300-2506

Pojawia się w:

Archives of Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 84.

Tytuł:

A Short Introduction to Stochastic Optimization

Autorzy:

Ombach, Jerzy

Powiązania:

https://bibliotekanauki.pl/articles/1373633.pdf

Data publikacji:

2014

Wydawca:

Uniwersytet Jagielloński. Wydawnictwo Uniwersytetu Jagiellońskiego

Tematy:

global optimization
stochastic algorithm
random search
convergence of metaheuristics

Opis:

We present some typical algorithms used for finding global minimum/ maximum of a function defined on a compact finite dimensional set, discuss commonly observed procedures for assessing and comparing the algorithms’ performance and quote theoretical results on convergence of a broad class of stochastic algorithms.

Źródło:

Schedae Informaticae; 2014, 23; 9-20
0860-0295
2083-8476

Pojawia się w:

Schedae Informaticae

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 85.

Tytuł:

Modelowanie metabolizmu w erze inżynierii biologicznej
Metabolic modelling in the era of biological engineering

Autorzy:

Boruta, T.
Bizukojć, M.
Ledakowicz, S.

Powiązania:

https://bibliotekanauki.pl/articles/2071697.pdf

Data publikacji:

2012

Wydawca:

Stowarzyszenie Inżynierów i Techników Mechaników Polskich

Tematy:

metabolizm
model
optymalizacja
bioinżynieria
algorytm
metabolism
optimization
bioengineering
algorithm

Opis:

Współczesna inżynieria metaboliczna oparta jest na narzędziach biologii systemów i biologii syntetycznej. Modelowanie matematyczne odgrywa istotną rolę w badaniach związanych z modyfikacją sieci metabolicznej, ponieważ pozwala w sposób ilościowy analizować system biologiczny. Analiza bilansu strumieni pozwala na wyznaczenie wartości strumieni w sieci poprzez maksymalizację biologicznej funkcji celu. Algorytmy inżynierii metabolicznej in silico oparte są na procedurach optymalizacji.
Modern metabolic engineering is based on the tools of systems biology and synthetic biology. Mathematical modelling plays an important role in the research related to metabolic network modification, because it enables one to analyze the biological system in a quantitative manner. The flux balance analysis enables one to determine flux values in the network by maximizing the biological objective function. Algorithms of in silico metabolic engineering are based on optimization procedures.

Źródło:

Inżynieria i Aparatura Chemiczna; 2012, 4; 89-91
0368-0827

Pojawia się w:

Inżynieria i Aparatura Chemiczna

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 86.

Tytuł:

Gold rush optimizer : a new population-based metaheuristic algorithm

Autorzy:

Zolf, Kamran

Powiązania:

https://bibliotekanauki.pl/articles/2204102.pdf

Data publikacji:

2023

Wydawca:

Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej

Tematy:

gold rush optimizer
metaheuristic
global optimization
population-based algorithm

Opis:

Today’s world is characterised by competitive environments, optimal resource utilization, and cost reduction, which has resulted in an increasing role for metaheuristic algorithms in solving complex modern problems. As a result, this paper introduces the gold rush optimizer (GRO), a population-based metaheuristic algorithm that simulates how gold-seekers prospected for gold during the Gold Rush Era using three key concepts of gold prospecting: migration, collaboration, and panning. The GRO algorithm is compared to twelve well-known metaheuristic algorithms on 29 benchmark test cases to assess the proposed approach’s performance. For scientific evaluation, the Friedman and Wilcoxon signed-rank tests are used. In addition to these test cases, the GRO algorithm is evaluated using three real-world engineering problems. The results indicated that the proposed algorithm was more capable than other algorithms in proposing qualitative and competitive solutions.

Źródło:

Operations Research and Decisions; 2023, 33, 1; 113--150
2081-8858
2391-6060

Pojawia się w:

Operations Research and Decisions

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 87.

Tytuł:

Analog Circuit Based on Computational Intelligence Techniques

Autorzy:

Oltean, G.
Hintea, S.
Şipos, E.

Powiązania:

https://bibliotekanauki.pl/articles/385049.pdf

Data publikacji:

2009

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

analog circuit design
optimization
genetic algorithm
neuro-fuzzy systems

Opis:

This paper presents a new method for analog circuit design optimization. Our approach turns to good account the advantages offered by computational intelligence techniques. Design objectives can be expressed in a flexible manner using fuzzy sets. This way appears the possibility to consider different degrees for requirement achievements and acceptability degree for a particular solution. Neuro-fuzzy systems (universal approximators) are used to model the complex multi-variable and nonlinear circuit performances. These models satisfy two main requirements: high accuracy and low computation complexity. An efficient and robust genetic algorithm does avoiding local minima the exploration of the large, multidimensional solution space in quest for the optimal solution.

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2009, 3, 2; 63-69
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 88.

Tytuł:

Scheduling of multiunit projects using tabu search algorithm

Autorzy:

Podolski, M.

Powiązania:

https://bibliotekanauki.pl/articles/347178.pdf

Data publikacji:

2015

Wydawca:

Akademia Wojsk Lądowych imienia generała Tadeusza Kościuszki

Tematy:

construction works scheduling
optimization
job scheduling
tabu search algorithm

Opis:

The paper describes problems of discrete optimization in scheduling of multiunit projects. A model of this kind of project with possibility of using many workgroups by the contractor has been presented. It leads to reduction of project duration. For solving NP-hard optimization problem, a tabu search algorithm has been applied in the model. The example of mod-el and application of the algorithm are also included in the paper.

Źródło:

Zeszyty Naukowe / Wyższa Szkoła Oficerska Wojsk Lądowych im. gen. T. Kościuszki; 2015, 1; 110-122
1731-8157

Pojawia się w:

Zeszyty Naukowe / Wyższa Szkoła Oficerska Wojsk Lądowych im. gen. T. Kościuszki

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 89.

Tytuł:

The application of genetic algorithm in the assignment problems in the transportation company

Autorzy:

Izdebski, M.
Jacyna, M.

Powiązania:

https://bibliotekanauki.pl/articles/247149.pdf

Data publikacji:

2018

Wydawca:

Instytut Techniczny Wojsk Lotniczych

Tematy:

assignment problem
genetic algorithm
multi-criterion optimization
transportation company

Opis:

The article presents the problem of the task assignment of the vehicles for the transportation company, which deals with the transport of the cargo in the full truckload system. The presented problem is a complex decision making issue which has not been analysed in the literature before. There must be passed through two stages in order to solve the task assignment problem of the vehicles for the transportation company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that perform these tasks. The task in the analysed problem is defined as transporting the cargo from the suppliers to the recipients. The transportation routes of the cargo must be determined. In order to solve the task assignment problem of the vehicles, the genetic algorithm has been developed. The construction stages of this algorithm are presented. The algorithm has been developed to solve the multi-criteria decision problem. What is more, the algorithm is verified by the use of the real input data.

Źródło:

Journal of KONES; 2018, 25, 4; 133-140
1231-4005
2354-0133

Pojawia się w:

Journal of KONES

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 90.

Tytuł:

Two stage optimization of the PMSM with excitation system composed of different materials

Autorzy:

Knypiński, Ł.
Nowak, L.

Powiązania:

https://bibliotekanauki.pl/articles/97722.pdf

Data publikacji:

2013

Wydawca:

Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej

Tematy:

electric machines
permanent magnet synchronous motor
optimization
genetic algorithm

Opis:

The paper presents the algorithm and software for the optimization of the rotor structure of the permanent magnet synchronous motor with magnet composed of two materials about different magnetic properties. The software consists of two modules: a numerical model of the PMSM motor and an optimization solver. Numerical implementation is based on finite element method. The optimization module has been elaborated employing the Delphi environment. For the rotor structure optimization the genetic algorithm has been applied Selected results of the calculation are presented and discussed.

Źródło:

Computer Applications in Electrical Engineering; 2013, 11; 148-158
1508-4248

Pojawia się w:

Computer Applications in Electrical Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 91.

Tytuł:

The Use of Heuristic Algorithms to Optimize the Transport Issues on the Example of Municipal Services Companies

Autorzy:

Izdebski, M.

Powiązania:

https://bibliotekanauki.pl/articles/223579.pdf

Data publikacji:

2014

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

municipal services companies
transport
optimization
genetic algorithm
ant algorithm
usługi komunalne
optymalizacja
algorytm genetyczny

Opis:

In this article the main optimization problems in the municipal services companies were presented. These problems concern the issue of vehicle routing. The mathematical models of these problems were described. The function of criterion and the conditions on designating the vehicle routing were defined. In this paper the hybrid algorithm solving the presented problems was proposed. The hybrid algorithm consists of two heuristic algorithms: the ant and the genetic algorithm. In this paper the stages of constructing of the hybrid algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process the roulette method was used and in the crossover process the operator PMX was presented. This algorithm was verified in programming language C #. The process of verification was divided into two stages. In the first stage the best parameters of the hybrid algorithm were designated. In the second stage the algorithm was started with these parameters and the result was compared with the random search algorithm. The random search algorithm generates 2000 routes and the best result is compared with the hybrid algorithm.

Źródło:

Archives of Transport; 2014, 29, 1; 27-36
0866-9546
2300-8830

Pojawia się w:

Archives of Transport

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 92.

Tytuł:

On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms

Autorzy:

El-Abd, M.

Powiązania:

https://bibliotekanauki.pl/articles/91658.pdf

Data publikacji:

2012

Wydawca:

Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych

Tematy:

Artificial Bee Colony Algorithm
ABC
particle swarm optimization (PSO)
PSO
hybridization
hybrid algorithm
CEC05

Opis:

In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Three different versions of the hybrid algorithm are tested in this work by experimenting with different selection mechanisms for the ABC component. All the algorithms are applied to the well-known CEC05 benchmark functions and compared based on three different metrics, namely, the solution reached, the success rate, and the performance rate.

Źródło:

Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 147-155
2083-2567
2449-6499

Pojawia się w:

Journal of Artificial Intelligence and Soft Computing Research

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 93.

Tytuł:

Quality improvement of a gear transmission by means of genetic algorithm

Autorzy:

Lempa, Paweł
Lisowski, Edward
Masui, Fumito
Filo, Grzegorz
Ptaszynski, Michal
Domagała, Mariusz
Fabiś-Domagała, Joanna

Powiązania:

https://bibliotekanauki.pl/articles/104043.pdf

Data publikacji:

2019

Wydawca:

Stowarzyszenie Menedżerów Jakości i Produkcji

Tematy:

optimization
genetic algorithm
gear transmission
optymalizacja
algorytm genetyczny
przekładnia zębata

Opis:

The article deals with the issue of quality improvement of a gear transmission by optimizing its geometry with the use of genetic algorithms. The optimization method is focused on increasing productivity and efficiency of the pump and reducing its pulsation. The best results are tested on mathematical model and automatically modelled in 3D be means of PTC Creo Software. The developed solution proved to be an effective tool in the search for better results, which greatly improved parameters of pump especially reduced flow pulsation.

Źródło:

Quality Production Improvement - QPI; 2019, 1, 1; 386-393
2657-8603

Pojawia się w:

Quality Production Improvement - QPI

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 94.

Tytuł:

Control Strategy of Parallel Systems with Efficiency Optimisation in Switched Reluctance Generators

Autorzy:

Zan, Xiaoshu
Lin, Hang
Xu, Guanqun
Zhao, Tiejun
Gong, Yi

Powiązania:

https://bibliotekanauki.pl/articles/1956008.pdf

Data publikacji:

2021

Wydawca:

Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej

Tematy:

switched reluctance generator
parallel system
efficiency optimization
differential evolution algorithm

Opis:

To solve motor heating and life shortening of parallel switched reluctance generator (SRG) induced by uneven output currents due to different external characteristics, we generally adopt current sharing control (CSC) to make each parallel generator undertake large load currents on average to improve the reliability of parallel power generation system. However, the method usually causes additional loss of power because it does not consider the efficiency characteristics of each parallel generator. Therefore, with the efficiency expression for the parallel system of SRG established and analysed, the control strategy based on differential evolution (DE) algorithm is proposed as a mechanism by which to enhance generating capacity and reliability of multi-machine power generation from the perspective of efficiency optimisation. We re-adjust the reference current of each parallel generator to transform the working point of each generator and implement the efficiency optimisation of parallel system. The performance of the proposed control method is evaluated in detail by the simulation and experiment, and comparison with traditional CSC is carried out as well.

Źródło:

Power Electronics and Drives; 2021, 6, 41; 61-74
2451-0262
2543-4292

Pojawia się w:

Power Electronics and Drives

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 95.

Tytuł:

Design of a Superconducting Antenna Integrated with a Diplexer for Radio-Astronomy Applications

Autorzy:

Donelli, M.
Febvre, P.

Powiązania:

https://bibliotekanauki.pl/articles/309365.pdf

Data publikacji:

2014

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Tematy:

diplexer
microwave antenna
optimization techniques
particle swarm algorithm
radio astronomy

Opis:

This paper presents the design of a compact frontend diplexer for radio-astronomy applications based on a self complementary Bow-tie antenna, a 3 dB T-junction splitter and two pass-band fractal lters. The whole diplexer structure has been optimized by using an evolutionary algorithm. In particular the problem of the diplexer design is recast into an optimization one by dening a suitable cost function which is then minimized by mean of an evolutionary algorithm namely the Particle Swarm Optimization (PSO). An X band diplexer prototype was fabricated and assessed demonstrating a good agreement between numerical and experimental results.

Źródło:

Journal of Telecommunications and Information Technology; 2014, 3; 113-118
1509-4553
1899-8852

Pojawia się w:

Journal of Telecommunications and Information Technology

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 96.

Tytuł:

Decision problem for a finite states change of semi-Markov process

Autorzy:

Grabski, F.

Powiązania:

https://bibliotekanauki.pl/articles/2069327.pdf

Data publikacji:

2015

Wydawca:

Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności

Tematy:

reliability
semi-Markov decision processes
optimization
Howard algorithm
linear programming

Opis:

In the paper there are presented basic concepts and some results of the theory of semi-Markov decision processes. The algorithm of optimization a SM decision process with a finite number of state changes is discussed here. The algorithm is based on a dynamic programming method. To clarify it the SM decision model for the maintenance operation is shown.

Źródło:

Journal of Polish Safety and Reliability Association; 2015, 6, 1; 95--100
2084-5316

Pojawia się w:

Journal of Polish Safety and Reliability Association

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 97.

Tytuł:

Optimal design of sandwich panels with a soft core
Optymalne projektowanie płyt warstwowych z miękkim rdzeniem

Autorzy:

Studziński, R.
Pozorski, Z.
Garstecki, A.

Powiązania:

https://bibliotekanauki.pl/articles/279446.pdf

Data publikacji:

2009

Wydawca:

Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej

Tematy:

sandwich panels
soft-core
Pareto optimization
soft computing
genetic algorithm

Opis:

The main issue taken up in the paper is to find optimal designs of multispan sandwich panels with slightly profiled steel facings and polyurethane foam core (PUR), which would satisfy conflicting demands of the market, i.e. minimal variance in types of panels, maximum range of application and minimum cost. The aim is to find dimensional and material parameters of panels which generate minimum cost and maximum length of span under prescribed loads in ultimate and serviceability limit states. The multi-criterion optimization problem is formulated in such a way, where the length of the span plays two roles, namely a design variable and a component of a vector objective function. An evolutionary algorithm is used. Numerous inequality constraints are introduced in two ways: directly and by external penalty functions.
Wpracy podejmuje się problem optymalizacji wieloprzęsłowych płyt warstwowych z rdzeniem z poliuretanu (PUR) i okładzinami stalowymi lekko profilowanymi. Poszukuje się rozwiązań, które spełnią sprzeczne wymagania rynku, mianowicie: minimalizację typoszeregu płyt, maksymalizację zakresu ich zastosowania oraz minimalizację kosztu produkcji. Celem optymalizacji jest znalezienie parametrów geometrycznych i materiałowych płyt warstwowych, które minimalizują koszt oraz maksymalizują dopuszczalną rozpiętość dla ustalonych obciążeń i przy spełnieniu stanów granicznych nośności i użytkowalności. W wielokryterialnym sformułowaniu problemu optymalizacyjnego rozpiętość pełni dwie funkcje. Jest ona równocześnie zmienną projektową i składową wektora funkcji celu. Jako narzędzie optymalizacji wykorzystano algorytmy genetyczne. Ograniczenia nierównościowe wprowadzono do procedury optymalizacyjnej za pomocą zewnętrznej funkcji kary oraz jawnie.

Źródło:

Journal of Theoretical and Applied Mechanics; 2009, 47, 3; 685-699
1429-2955

Pojawia się w:

Journal of Theoretical and Applied Mechanics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 98.

Tytuł:

Fireworks Algorithm for Unconstrained Function Optimization Problems

Autorzy:

Baidoo, E.

Powiązania:

https://bibliotekanauki.pl/articles/117784.pdf

Data publikacji:

2017

Wydawca:

Polskie Towarzystwo Promocji Wiedzy

Tematy:

Fireworks algorithm
Function optimization
swarm intelligence
Mathematical programming
Natural computing

Opis:

Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard ben-chmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended expe-rimentation. Additionally, this paper validates the effect of runtime on the al-gorithm performance.

Źródło:

Applied Computer Science; 2017, 13, 1; 61-74
1895-3735

Pojawia się w:

Applied Computer Science

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 99.

Tytuł:

Optimization of the impact multi-mass vibration absorbers

Autorzy:

Kernytskyy, I.
Diveyev, B.
Horbaj, O.
Hlobchak, M.
Kopytko, M.
Zachek, O.

Powiązania:

https://bibliotekanauki.pl/articles/886928.pdf

Data publikacji:

2017

Wydawca:

Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie

Tematy:

impact damping system
multi-mass
dynamic vibration absorber
optimization
simultaneous optimization
genetic algorithm
Boltzmann approximation

Opis:

Optimization of the impact multi-mass vibration absorbers. The problem of attaching dynamic vibration absorber (DVA) to a discrete multi-degree-of-freedom or continuous structure has been outlined in many papers and monographs. An impact damping system can overcome some limitations by impact as the damping medium and impact mass interaction as the damping mechanism. The paper contemplates the provision of DVA with the several of the impact masses. Such originally designed absorbers reduce vibration selectively in maximum vibration mode without introducing vibration in other modes. An impact damper is a passive control device which takes the form of a freely moving mass, constrained by stops attached to the structure under control, i.e. the primary structure. The damping results from the exchange of momentum during impacts between the mass and the stops as the structure vibrates. The paper contemplates the provision of the impact multi-mass DVA’s with masses collisions for additional damping. For some cases of DVA optimization such a design seems more effective than conventional multi-mass DVA with independent mass moving. A technique is developed to give the optimal DVA’s for the elimination of excessive vibration in harmonic stochastic and impact loaded systems.

Źródło:

Scientific Review Engineering and Environmental Sciences; 2017, 26, 3[77]
1732-9353

Pojawia się w:

Scientific Review Engineering and Environmental Sciences

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 100.

Tytuł:

On the efficiency of population-based optimization in finding best parameters for RGB-D visual odometry

Autorzy:

Kostusiak, Aleksander
Skrzypczyński, Piotr

Powiązania:

https://bibliotekanauki.pl/articles/384397.pdf

Data publikacji:

2019

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów

Tematy:

particle swarm optimization (PSO)
evolutionary algorithm
visual odometry
RGB-D

Opis:

Visual odometry estimates the transformations between consecutive frames of a video stream in order to recover the camera’s trajectory. As this approach does not require to build a map of the observed environment, it is fast and simple to implement. In the last decade RGBD cameras proliferated in roboTIcs, being also the sensors of choice for many practical visual odometry systems. Although RGB-D cameras provide readily available depth images, that greatly simplify the frame-to-frame transformations computaTIon, the number of numerical parameters that have to be set properly in a visual odometry system to obtain an accurate trajectory estimate remains high. Whereas seƫng them by hand is certainly possible, it is a tedious try-and-error task. Therefore, in this article we make an assessment of two population-based approaches to parameter opTImizaTIon, that are for long time applied in various areas of robotics, as means to find best parameters of a simple RGB-D visual odometry system. The optimization algorithms investigated here are particle swarm optimization and an evolutionary algorithm variant. We focus on the optimization methods themselves, rather than on the visual odometry algorithm, seeking an efficient procedure to find parameters that minimize the estimated trajectory errors. From the experimental results we draw conclusions as to both the efficiency of the optimization methods, and the role of particular parameters in the visual odometry system.

Źródło:

Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 2; 5-14
1897-8649
2080-2145

Pojawia się w:

Journal of Automation Mobile Robotics and Intelligent Systems

Dostawca treści:

Biblioteka Nauki

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