Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm
Convoluted high-order structures as modeled through mathematical principle including telecommunication systems, power plants for urbanized energy supply and aerospace systems are often accompanied by the apparent setbacks in analyzing, experimentation and operational control. The complexity of s...
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Online Access: | http://irep.iium.edu.my/108280/7/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation.pdf http://irep.iium.edu.my/108280/8/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation_Scopus.pdf http://irep.iium.edu.my/108280/ https://ieeexplore.ieee.org/document/10227161 https://doi.org/10.1109/ICSSE58758.2023.10227161 |
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my.iium.irep.1082802023-11-21T07:49:31Z http://irep.iium.edu.my/108280/ Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm Suid, Mohd Helmi Ahmad, Mohd Ashraf Ahmad, Salmiah Ghazali, Mohd Riduwan Tumari, Mohd Zaidi TJ212 Control engineering Convoluted high-order structures as modeled through mathematical principle including telecommunication systems, power plants for urbanized energy supply and aerospace systems are often accompanied by the apparent setbacks in analyzing, experimentation and operational control. The complexity of such structures is proposedly decreased within the current study through introduction of a hybridized meta-heuristics fine-tuning approach between Adaptive Safe Experimentation Dynamics (ASED) and Nonlinear Sine Cosine Algorithm (NSCA). Entrapment within the local optima is hereby overcome through ASED by adaptive random perturbation, with improved exploration and exploitation of the introduced approach being further enabled by NSCA. The method’s potency was evaluated through an empirically adopted 6th order numerical function. Experimentation outcomes uncovered profound robustness and consistency from ASED-NSCA against alternative modern optimization-based techniques towards comparatively outstanding model order reduction (MOR). IEEE 2023-08-29 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/108280/7/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation.pdf application/pdf en http://irep.iium.edu.my/108280/8/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation_Scopus.pdf Suid, Mohd Helmi and Ahmad, Mohd Ashraf and Ahmad, Salmiah and Ghazali, Mohd Riduwan and Tumari, Mohd Zaidi (2023) Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm. In: 2023 International Conference on System Science and Engineering (ICSSE), 27-28 August 2023, Ho Chi Minh, Vietnam. https://ieeexplore.ieee.org/document/10227161 https://doi.org/10.1109/ICSSE58758.2023.10227161 |
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TJ212 Control engineering Suid, Mohd Helmi Ahmad, Mohd Ashraf Ahmad, Salmiah Ghazali, Mohd Riduwan Tumari, Mohd Zaidi Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
description |
Convoluted high-order structures as modeled through mathematical principle including telecommunication systems, power plants for urbanized energy supply and
aerospace systems are often accompanied by the apparent
setbacks in analyzing, experimentation and operational control. The complexity of such structures is proposedly decreased within the current study through introduction of a hybridized meta-heuristics fine-tuning approach between Adaptive Safe Experimentation Dynamics (ASED) and Nonlinear Sine Cosine Algorithm (NSCA). Entrapment within the local optima is hereby overcome through ASED by adaptive random perturbation, with improved exploration and exploitation of the introduced approach being further enabled by NSCA. The method’s potency was evaluated through an empirically adopted 6th order numerical function. Experimentation outcomes uncovered profound robustness and consistency from ASED-NSCA against alternative modern optimization-based techniques towards comparatively outstanding model order reduction (MOR). |
format |
Proceeding Paper |
author |
Suid, Mohd Helmi Ahmad, Mohd Ashraf Ahmad, Salmiah Ghazali, Mohd Riduwan Tumari, Mohd Zaidi |
author_facet |
Suid, Mohd Helmi Ahmad, Mohd Ashraf Ahmad, Salmiah Ghazali, Mohd Riduwan Tumari, Mohd Zaidi |
author_sort |
Suid, Mohd Helmi |
title |
Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
title_short |
Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
title_full |
Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
title_fullStr |
Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
title_full_unstemmed |
Optimal model order reduction based on Hybridization of Adaptive Safe Experimentation Dynamics-Nonlinear Sine Cosine Algorithm |
title_sort |
optimal model order reduction based on hybridization of adaptive safe experimentation dynamics-nonlinear sine cosine algorithm |
publisher |
IEEE |
publishDate |
2023 |
url |
http://irep.iium.edu.my/108280/7/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation.pdf http://irep.iium.edu.my/108280/8/108280_Optimal%20model%20order%20reduction%20based%20on%20Hybridization%20of%20Adaptive%20Safe%20Experimentation_Scopus.pdf http://irep.iium.edu.my/108280/ https://ieeexplore.ieee.org/document/10227161 https://doi.org/10.1109/ICSSE58758.2023.10227161 |
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1783876128277004288 |
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13.160551 |