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A mating technique for various crossover in genetic algorithm for optimum system identification

System identification is the study involving the derivation of a mathematical model from input and output data to explain dynamical behavior of a system. Such derivation is made using a mathematical model based on certain specified assumptions. To researchers who are involved in the application of G...

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Main Authors: Abd Samad @ Mahmood, Md Fahmi, Zainuddin, Farah Ayiesya
Format: Article
Language:English
Published: Praise Worthy Prize 2021
Online Access:http://eprints.utem.edu.my/id/eprint/26735/2/21102-47870-1-PB.PDF
http://eprints.utem.edu.my/id/eprint/26735/
https://www.praiseworthyprize.org/jsm/index.php?journal=ireme&page=article&op=view&path%5B%5D=26010
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spelling my.utem.eprints.267352024-04-26T08:36:04Z http://eprints.utem.edu.my/id/eprint/26735/ A mating technique for various crossover in genetic algorithm for optimum system identification Abd Samad @ Mahmood, Md Fahmi Zainuddin, Farah Ayiesya System identification is the study involving the derivation of a mathematical model from input and output data to explain dynamical behavior of a system. Such derivation is made using a mathematical model based on certain specified assumptions. To researchers who are involved in the application of Genetic Algorithm (GA) in optimization, the process of choosing the best parents in the population for mating has become of great interest. Here, the application is on selecting a model structure for system identification. This step addresses selecting an adequate model, i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. This paper demonstrates the integration of a novel mating technique with various types of crossover to enhance the performance of GA application. Four discrete-time systems of linear and nonlinear types are simulated and identified. The results show that GA with single parent mating can speed up the search for optimal models and avoid premature convergence even with different types of crossover. Praise Worthy Prize 2021-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/26735/2/21102-47870-1-PB.PDF Abd Samad @ Mahmood, Md Fahmi and Zainuddin, Farah Ayiesya (2021) A mating technique for various crossover in genetic algorithm for optimum system identification. International Review of Mechanical Engineering, 15 (11). pp. 574-581. ISSN 1970 - 8734 https://www.praiseworthyprize.org/jsm/index.php?journal=ireme&page=article&op=view&path%5B%5D=26010 10.15866/ireme.v15i11.21102
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description System identification is the study involving the derivation of a mathematical model from input and output data to explain dynamical behavior of a system. Such derivation is made using a mathematical model based on certain specified assumptions. To researchers who are involved in the application of Genetic Algorithm (GA) in optimization, the process of choosing the best parents in the population for mating has become of great interest. Here, the application is on selecting a model structure for system identification. This step addresses selecting an adequate model, i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. This paper demonstrates the integration of a novel mating technique with various types of crossover to enhance the performance of GA application. Four discrete-time systems of linear and nonlinear types are simulated and identified. The results show that GA with single parent mating can speed up the search for optimal models and avoid premature convergence even with different types of crossover.
format Article
author Abd Samad @ Mahmood, Md Fahmi
Zainuddin, Farah Ayiesya
spellingShingle Abd Samad @ Mahmood, Md Fahmi
Zainuddin, Farah Ayiesya
A mating technique for various crossover in genetic algorithm for optimum system identification
author_facet Abd Samad @ Mahmood, Md Fahmi
Zainuddin, Farah Ayiesya
author_sort Abd Samad @ Mahmood, Md Fahmi
title A mating technique for various crossover in genetic algorithm for optimum system identification
title_short A mating technique for various crossover in genetic algorithm for optimum system identification
title_full A mating technique for various crossover in genetic algorithm for optimum system identification
title_fullStr A mating technique for various crossover in genetic algorithm for optimum system identification
title_full_unstemmed A mating technique for various crossover in genetic algorithm for optimum system identification
title_sort mating technique for various crossover in genetic algorithm for optimum system identification
publisher Praise Worthy Prize
publishDate 2021
url http://eprints.utem.edu.my/id/eprint/26735/2/21102-47870-1-PB.PDF
http://eprints.utem.edu.my/id/eprint/26735/
https://www.praiseworthyprize.org/jsm/index.php?journal=ireme&page=article&op=view&path%5B%5D=26010
_version_ 1800103267869392896
score 13.211869

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