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Wyświetlanie 1-15 z 272
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
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
Artykuł
Wyświetlanie 1-15 z 272

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