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Tytuł:
Genetic algorithms-aided reliability analysis
Autorzy:
Harnpornchai, N.
Powiązania:
https://bibliotekanauki.pl/articles/2069699.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:
genetic algorithms
reliability analysis
simulation methods
complex systems
multiple failure modes
Opis:
A hybrid procedure of Genetic Algorithms (GAs) and reliability analysis is described, discussed, and summarized. The procedure is specifically referred to as a Genetic Algorithms-aided (GAs-aided) reliability analysis. Two classes of GAs, namely simple GAs and multimodal GAs, are introduced to solve a number of important problems in reliability analysis. The problems cover the determination of Point of Maximum Likelihood in failure domain (PML), the computation of failure probability using the GAs-determined PML, and the determination of multiple design points. The MCS-based method using the GAs-determined PML is specifically implemented in the so-called an Importance Sampling around PML (ISPML). The application of GAs to each respective problem is then demonstrated via numerical examples in order to clarify the procedures. With an aid from GAs, reliability analysis is possible even if there is no information about the geometry or landscape of limit state surfaces and the total number of crucial likelihood points. In addition, GAs significantly improve the computational efficiency and realize the analysis of rare events under constrained computational resources. The implementation of GAs to reliability analysis for building up the hybrid procedure is readily because of their algorithmic simplicity.
Źródło:
Journal of Polish Safety and Reliability Association; 2009, 1; 145--156
2084-5316
Pojawia się w:
Journal of Polish Safety and Reliability Association
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithms in fatigue crack detection
Autorzy:
Krawczuk, M.
Żak, A.
Ostachowicz, W.
Powiązania:
https://bibliotekanauki.pl/articles/279846.pdf
Data publikacji:
2001
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
fatigue crack detection
vibration methods
genetic algorithms
Opis:
This paper presents results identification of fatigue cracks in beams via genetic search technique and changes in natural frequencies. The location and size of the crack are determined by minimisation of an errorfunction involving the difference between the calculated and "measured" natural frequencies. The simulation studies indicate that the changes in the natural frequencies and genetic algorithm allows one to estimate the fatigue crack parameters (location and size) very accurately and fast.
Algorytmy genetyczne w detekcji pęknięć zmęczeniowych. W pracy przedstawiono wyniki identyfikacji położenia i wielkości pęknięć zmęczeniowych metodą algorytmów genetycznych z wykorzystaniem zmian częstości drgań własnych. Położenie i wielkość pęknięcia poszukiwano minimalizując funkcję celu wykorzystując różnice między częstościami mierzonymi i obliczanymi. Wyniki symulacji wskazują, że zmiany częstości drgań własnych i algorytm genetyczny pozwalają wyznaczać parametry pęknięcia zmęczeniowego (położenie i wielkość) szybko i dokładnie.
Źródło:
Journal of Theoretical and Applied Mechanics; 2001, 39, 4; 815-823
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive approaches to parameter control in genetic algorithms and genetic programming
Autorzy:
Spalek, J.
Gregor, M.
Powiązania:
https://bibliotekanauki.pl/articles/117900.pdf
Data publikacji:
2011
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
adaptive approach
genetic algorithms
genetic programming
Opis:
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks such as automated design of control systems, where the space of solutions is non-trivial and may contain discontinuities. Several adaptive mechanisms for control of the search algorithm's parameters are proposed, investigated and compared to each other. It is shown that the proposed mechanisms are useful in preventing the search from getting trapped in local extremes of the fitness landscape.
Źródło:
Applied Computer Science; 2011, 7, 1; 38-56
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive switching of mutation rate for genetic algorithms and genetic programming
Autorzy:
Spalek, J.
Gregor, M.
Powiązania:
https://bibliotekanauki.pl/articles/118223.pdf
Data publikacji:
2011
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
genetic algorithms
genetic programming
adaptive mechanism
Opis:
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks such as automated design of control systems, where the space of solutions is non-trivial and may contain discontinuities. An adaptive value-switching mechanism for mutation rate control is proposed. It is shown that the proposed mechanism is useful in preventing the search from getting trapped in local extremes of the fitness landscape.
Źródło:
Applied Computer Science; 2011, 7, 1; 30-37
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Solving the abstract planning problem using genetic algorithms
Autorzy:
Skaruz, J.
Niewiadomski, A.
Penczek, W.
Powiązania:
https://bibliotekanauki.pl/articles/93024.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
abstract planning
genetic algorithms
web service composition
Opis:
The paper presents a new approach based on genetic algorithms to the abstract planning problem, which is the first stage of the web service composition problem. An abstract plan is defined as an equivalence class of sequences of service types that satisfy a user query. Intuitively, two sequences are equivalent if they are composed of the same service types, but not necessarily occurring in the same order. The objective of our genetic algorithm (GA) is to return representatives of abstract plans without generating all the equivalent sequences. The paper presents experimental results compared with the results obtained from SMT-solver, which show that GA finds solutions for very large sets of service types in a reasonable time.
Źródło:
Studia Informatica : systems and information technology; 2013, 1-2(17); 29-48
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithms in pseudorandom testing of medical digitalcircuits
Autorzy:
Chodacki, M.
Michalski, D.
Powiązania:
https://bibliotekanauki.pl/articles/333138.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
algorytmy genetyczne
urządzenia medyczne
symulacja układów cyfrowych
genetic algorithms
medical devices
simulation of digital circuits
pseudorandom testing
Opis:
In this paper the problem of unsatisfactory diagnostic efficiency of pseudorandom testing (PRT) technique used to detect faults of digital circuits in testing medical systems of critical importance is presented. The simulations have revealed a weakness of commonly used PRT technique that generally does not assure that all stuck at faults are detected. Thus, it is suggested that PRT technique should be supplemented with additional deterministic testing sequences to enhance fault detection. To design built-in selftesting (BIST) structures a genetic algorithm and digital system stochastic model were used. By employing the stochastic model it is possible to reduce considerably the computer simulation time required for BIST architecture design. In particular, an effect of proportional and ranking selections on the convergence of genetic algorithm in searching for a globally optimal solution, while maintaining the diversity of the population of individuals and limiting its premature stagnation.
Źródło:
Journal of Medical Informatics & Technologies; 2009, 13; 209-214
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of genetic algorithms to the traveling salesman problem
Autorzy:
Sikora, Tomasz
Gryglewicz-Kacerka, Wanda
Powiązania:
https://bibliotekanauki.pl/articles/30148246.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
evolutionary algorithms
genetic algorithms
traveling salesman problem
TSP
Opis:
The purpose of this paper was to investigate in practice the possibility of using evolutionary algorithms to solve the traveling salesman problem on a real example. The goal was achieved by developing an original implementation of the evolutionary algorithm in Python, and by preparing an example of the traveling salesman problem in the form of a directed graph representing Polish voivodship cities. As part of the work an application in Python was written. It provides a user interface which allows to set selected parameters of the evolutionary algorithm and solve the prepared problem. The results are presented in both text and graphical form. The correctness of the evolutionary algorithm's operation and the implementation was confirmed by performed tests. A large number of tested solutions (2500) and the analysis of the obtained results allowed for a conclusion that an optimal (relatively suboptimal) solution was found.
Źródło:
Applied Computer Science; 2023, 19, 2; 55-62
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Genetic Algorithms in Design of Public Transport Network
Autorzy:
Lesiak, Piotr
Bojarczak, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/504669.pdf
Data publikacji:
2015
Wydawca:
Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:
genetic algorithms
search methods
optimization
transportation problems
Opis:
The paper presents possibilities of application of genetic algorithms in design of public transport network. Transportation tasks such as determination of optimal routes and timetable for means of transport belong to difficult complex optimization problems, therefore they cannot be solved using traditional search algorithms. It turns out that genetic algorithms can be very useful to solve these transportation problem.
Źródło:
Logistics and Transport; 2015, 26, 2; 75-82
1734-2015
Pojawia się w:
Logistics and Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of genetic algorithms for the estimation of hydraulic conductivity
Autorzy:
Bartlewska-Urban, M.
Strzelecki, T.
Powiązania:
https://bibliotekanauki.pl/articles/178471.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
genetic algorithms
hydraulic conductivity
Biot consolidation model
Opis:
In the study described here model calibration was performed employing the inverse analysis using genetic algorithms (GA). The objective of analysis is to determine value of the coefficient of hydraulic conductivity, k. The commonly used method for the determination of coefficient of hydraulic conductivity based on Terzaghi consolidation leads to an underestimation of the value of k as the Terzaghi model does not take into account the deformation of soil skeleton. Here, an alternative methodology based on genetic algorithms is presented for the determination of the basic parameters of Biot consolidation model. It has been demonstrated that genetic algorithms are a highly effective tool enabling automatic calibration based on simple rules. The values of the coefficient of hydraulic conductivity obtained with GA are of at least one order smaller than values obtained with the Terzaghi model.
Źródło:
Studia Geotechnica et Mechanica; 2018, 40, 2; 140-146
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of Job Shop Scheduling Problem by Genetic Algorithms: Case Study
Autorzy:
Sahar, Habbadi
Herrou, Brahim
Sekkat, Souhail
Powiązania:
https://bibliotekanauki.pl/articles/24200523.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
optimization
metaheuristics
scheduling
job shop scheduling problem
genetic algorithms
simulation
Opis:
The Job Shop scheduling problem is widely used in industry and has been the subject of study by several researchers with the aim of optimizing work sequences. This case study provides an overview of genetic algorithms, which have great potential for solving this type of combinatorial problem. The method will be applied manually during this study to understand the procedure and process of executing programs based on genetic algorithms. This problem requires strong decision analysis throughout the process due to the numerous choices and allocations of jobs to machines at specific times, in a specific order, and over a given duration. This operation is carried out at the operational level, and research must find an intelligent method to identify the best and most optimal combination. This article presents genetic algorithms in detail to explain their usage and to understand the compilation method of an intelligent program based on genetic algorithms. By the end of the article, the genetic algorithm method will have proven its performance in the search for the optimal solution to achieve the most optimal job sequence scenario.
Źródło:
Management and Production Engineering Review; 2023, 14, 3; 44--56
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multiobjective optimization of multipass turning machining process using the Genetic Algorithms solution
Autorzy:
Amiolemhen, Patrick Ejebheare
Eseigbe, Joshua Ahurome
Powiązania:
https://bibliotekanauki.pl/articles/95335.pdf
Data publikacji:
2019
Wydawca:
Politechnika Koszalińska. Wydawnictwo Uczelniane
Tematy:
turning process
genetic algorithms
minimum production cost
minimum production time
single-objective model
multi-objective model
toczenie
proces toczenia
algorytmy genetyczne
minimalny koszt produkcji
minimalny czas produkcji
model wielokryterialny
Opis:
The study involves the development of multi-objective optimization model for turning machining process. This model was developed using a GA - based weighted-sum of minimum production cost and time criteria of multipass turning machining process subject to relevant technological/practical constraints. The results of the single-objective machining process optimization models for the multipass turning machining process when compared with those of multi-objective machining process model yielded the minimum production cost and minimum production time as $5.775 and 8.320 min respectively (and the corresponding production time and production cost as 12.996 min and $6.992, respectively), while those of the multi-objective machining process optimization model were $5.841and 9.097 min. Thus, the multi-objective machining process optimization model performed better than each of the single-objective model for the two criteria of minimum production cost and minimum production time respectively. The results also show that minimum production time model performs better than the minimum production cost model. For the example considered, the multi-objective model gave a lower production time of 30.0% than the corresponding production time obtained from the minimum production cost model, while it gave a lower production cost of 16.46% than the corresponding cost obtained by the minimum production time model.
Źródło:
Journal of Mechanical and Energy Engineering; 2019, 3, 2; 97-108
2544-0780
2544-1671
Pojawia się w:
Journal of Mechanical and Energy Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-strategy navigation for a mobile data acquisition platform using genetic algorithms
Autorzy:
Halal, F.
Zaremba, M. B.
Powiązania:
https://bibliotekanauki.pl/articles/950950.pdf
Data publikacji:
2017
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
genetic algorithms
path planning
monitoring system
remote sensing
navigation control
heuristic search
Opis:
Monitoring of biological and chemical pollutants in large bodies of water requires the acquisition of a large number of in-situ measurements by a mobile sensor platform. Critical to this problem is an efficient path planning method, easily adaptable to different control strategies that ensure the collection of data of the greatest value. This paper proposes a deliberative path planning algorithm, which features the use of waypoints for a ship navigation trajectory that are generated by Genetic Algorithm (GA) based procedures. The global search abilities of Genetic Algorithms are combined with the heuristic local search in order to implement a navigation behaviour suitable to the required data collection strategy. The adaptive search system operates on multi-layer maps generated from remote sensing data, and provides the capacity for dealing with multiple classes of water pollutants. A suitable objective function was proposed to handle different sampling strategies for the collection of samples from multiple water pollutant classes. A region-of-interest (ROI) component was introduced to deal effectively with the large scale of search environments by pushing the search towards ROI zones. This resulted in the reduction of the search time and the computing cost, as well as good convergence to an optimal solution. The global path planning performance was further improved by multipoint crossover operators running in each GA generation. The system was developed and tested for inland water monitoring and trajectory planning of a mobile sample acquisition platform using commercially available satellite data.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2017, 11, 1; 30-41
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithms for classifiers training sets optimisation applied to human face recognition
Autorzy:
Kawulok, M.
Powiązania:
https://bibliotekanauki.pl/articles/333826.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
maszyna wektorów nośnych
algorytmy genetyczne
rozpoznawanie twarzy człowieka
support vector machines
genetic algorithms
human face recognition
Opis:
Human face recognition is a multi-stage process within which many classification problems must be solved. This is performed by learning machines which elaborate classification rules based on a given training set. Therefore, one of the most important issues is selection of a training set which would properly represent the data that will be further classified. This paper presents an approach which utilizes genetic algorithms for selecting classifiers' training sets. This approach was implemented for the Support Vector Machines which is applied in two areas of automatic human face recognition: face verification and feature vectors comparison. Effectiveness of the presented concept was confirmed with appropriate experiments which results are described in this paper.
Źródło:
Journal of Medical Informatics & Technologies; 2007, 11; 135-143
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithms solution to the single-objective machining process optimization time model
Autorzy:
Amiolemhen, Patrick
Eseigbe, Joshua
Powiązania:
https://bibliotekanauki.pl/articles/95251.pdf
Data publikacji:
2019
Wydawca:
Politechnika Koszalińska. Wydawnictwo Uczelniane
Tematy:
production time
optimization
machining model
genetic algorithms
development
czas produkcji
optymalizacja
obróbka
algorytmy genetyczne
rozwój
Opis:
Minimum Production Time model of the machining process optimization problem comprising seven lathe machining operations were developed using Genetic Algorithms solution method. The various cost and time components involved in the minimum production cost and minimum production time criteria respectively, as well as all relevant technological/practical constraints were determined. An interactive, user-friendly computer package was then developed in Microsoft Visual Basic.Net environment to implement the developed models. The package was used to determine optimal machining parameters of cutting speed, feed rate and depth of cut for the seven machining operations with twenty-three technological constraints in the conversion of a cylindrical metal bar stock into a finished machined profile. The result of the single-objective machining process optimization models shows that the minimum production time is 21.84 min.
Źródło:
Journal of Mechanical and Energy Engineering; 2019, 3, 1; 13-23
2544-0780
2544-1671
Pojawia się w:
Journal of Mechanical and Energy Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Use of Genetic Algorithms for Searching Parameter Space in Gaussian Process Modeling
Autorzy:
Krok, A.
Powiązania:
https://bibliotekanauki.pl/articles/308239.pdf
Data publikacji:
2015
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
Gaussian processes
genetic algorithms
Opis:
The aim of the paper is to present the possibilities of modeling the experimental data by Gaussian processes. Genetic algorithms are used for finding the Gaussian process parameters. Comparison of data modeling accuracy is made according to neural networks learned by Kalman filtering. Concrete hysteresis loops obtained by the experiment of cyclic loading are considered as the real data time series.
Źródło:
Journal of Telecommunications and Information Technology; 2015, 3; 58-63
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 159

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