Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling
This paper presents perturbation parameters for tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. The perturbation of the proposed algorithm was composed of crossover and mutation operators. Initially, a set of parameter values was tuned vi...
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Online Access: | http://eprints.utm.my/id/eprint/58814/1/HishamuddinJamaluddin2015_PerturbationParametersTuningofMultiObjective.pdf http://eprints.utm.my/id/eprint/58814/ http://dx.doi.org/10.11113/jt.v75.5335 |
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my.utm.588142021-12-19T02:54:40Z http://eprints.utm.my/id/eprint/58814/ Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling Zakaria, Mohd. Zakimi Jamaluddin, Hishamuddin Ahmad, Robiah Harun, Azmi Hussin, Radhwan Mohd. Khalil, Ahmad Nabil Md. Naim, Muhammad Khairy Annuar, Ahmad Faizal TJ Mechanical engineering and machinery This paper presents perturbation parameters for tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. The perturbation of the proposed algorithm was composed of crossover and mutation operators. Initially, a set of parameter values was tuned vigorously by executing multiple runs of algorithm for each proposed parameter variation. A set of values for crossover and mutation rates were proposed in executing the algorithm for model structure selection in dynamic system modeling. The model structure selection was one of the procedures in the system identification technique. Most researchers focused on the problem in selecting the parsimony model as the best represented the dynamic systems. Therefore, this problem needed two objective functions to overcome it, i.e. minimum predictive error and model complexity. One of the main problems in identification of dynamic systems is to select the minimal model from the huge possible models that need to be considered. Hence, the important concepts in selecting good and adequate model used in the proposed algorithm were elaborated, including the implementation of the algorithm for modeling dynamic systems. Besides, the results showed that multi-objective optimization differential evolution performed better with tuned perturbation parameters. Penerbit UTM Press 2015-09-03 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/58814/1/HishamuddinJamaluddin2015_PerturbationParametersTuningofMultiObjective.pdf Zakaria, Mohd. Zakimi and Jamaluddin, Hishamuddin and Ahmad, Robiah and Harun, Azmi and Hussin, Radhwan and Mohd. Khalil, Ahmad Nabil and Md. Naim, Muhammad Khairy and Annuar, Ahmad Faizal (2015) Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. Jurnal Teknologi, 75 (11). pp. 77-90. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v75.5335 DOI:10.11113/jt.v75.5335 |
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TJ Mechanical engineering and machinery Zakaria, Mohd. Zakimi Jamaluddin, Hishamuddin Ahmad, Robiah Harun, Azmi Hussin, Radhwan Mohd. Khalil, Ahmad Nabil Md. Naim, Muhammad Khairy Annuar, Ahmad Faizal Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
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This paper presents perturbation parameters for tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. The perturbation of the proposed algorithm was composed of crossover and mutation operators. Initially, a set of parameter values was tuned vigorously by executing multiple runs of algorithm for each proposed parameter variation. A set of values for crossover and mutation rates were proposed in executing the algorithm for model structure selection in dynamic system modeling. The model structure selection was one of the procedures in the system identification technique. Most researchers focused on the problem in selecting the parsimony model as the best represented the dynamic systems. Therefore, this problem needed two objective functions to overcome it, i.e. minimum predictive error and model complexity. One of the main problems in identification of dynamic systems is to select the minimal model from the huge possible models that need to be considered. Hence, the important concepts in selecting good and adequate model used in the proposed algorithm were elaborated, including the implementation of the algorithm for modeling dynamic systems. Besides, the results showed that multi-objective optimization differential evolution performed better with tuned perturbation parameters. |
format |
Article |
author |
Zakaria, Mohd. Zakimi Jamaluddin, Hishamuddin Ahmad, Robiah Harun, Azmi Hussin, Radhwan Mohd. Khalil, Ahmad Nabil Md. Naim, Muhammad Khairy Annuar, Ahmad Faizal |
author_facet |
Zakaria, Mohd. Zakimi Jamaluddin, Hishamuddin Ahmad, Robiah Harun, Azmi Hussin, Radhwan Mohd. Khalil, Ahmad Nabil Md. Naim, Muhammad Khairy Annuar, Ahmad Faizal |
author_sort |
Zakaria, Mohd. Zakimi |
title |
Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
title_short |
Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
title_full |
Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
title_fullStr |
Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
title_full_unstemmed |
Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
title_sort |
perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling |
publisher |
Penerbit UTM Press |
publishDate |
2015 |
url |
http://eprints.utm.my/id/eprint/58814/1/HishamuddinJamaluddin2015_PerturbationParametersTuningofMultiObjective.pdf http://eprints.utm.my/id/eprint/58814/ http://dx.doi.org/10.11113/jt.v75.5335 |
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1720436890875723776 |