The Experts below are selected from a list of 14328 Experts worldwide ranked by ideXlab platform
F H F Leung - One of the best experts on this subject based on the ideXlab platform.
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IEEE Congress on Evolutionary Computation - A new Differential Evolution with Wavelet Theory based mutation operation
2009 IEEE Congress on Evolutionary Computation, 2009Co-Authors: J.c.y. Lai, F H F Leung, Sai Ho LingAbstract:An improved Differential Evolution (DE) that incorporates a Wavelet-based mutation operation to control the scaling factor is proposed. The Wavelet Theory applied is to enhance DE in exploring the solution spaces more effectively for better solutions. A suite of benchmark test functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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a new hybrid particle swarm optimization with Wavelet Theory based mutation operation
Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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IEEE Congress on Evolutionary Computation - A new hybrid Particle Swarm Optimization with Wavelet Theory based mutation operation
2007 IEEE Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
Sai Ho Ling - One of the best experts on this subject based on the ideXlab platform.
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IEEE Congress on Evolutionary Computation - A new Differential Evolution with Wavelet Theory based mutation operation
2009 IEEE Congress on Evolutionary Computation, 2009Co-Authors: J.c.y. Lai, F H F Leung, Sai Ho LingAbstract:An improved Differential Evolution (DE) that incorporates a Wavelet-based mutation operation to control the scaling factor is proposed. The Wavelet Theory applied is to enhance DE in exploring the solution spaces more effectively for better solutions. A suite of benchmark test functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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a new hybrid particle swarm optimization with Wavelet Theory based mutation operation
Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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IEEE Congress on Evolutionary Computation - A new hybrid Particle Swarm Optimization with Wavelet Theory based mutation operation
2007 IEEE Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
Hamid A. Toliyat - One of the best experts on this subject based on the ideXlab platform.
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Synchronous Generators Stator Ground Fault Detection Using Wavelet Theory
IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, 2018Co-Authors: Khaled Al Jaafari, Amir Negahdari, Hamid A. ToliyatAbstract:In this paper, a novel stator ground fault detection method based on Wavelet Theory is tested on a lab scale synchronous generator. The lab scale setup is used to mimic the real power generation system and to simulate the fault characteristics particularly at or near the generator neutral of large industrial generators. The experimental results prove the capability of the Wavelet algorithm in synchronous generators stator winding ground fault detection.
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IECON - Synchronous Generators Stator Ground Fault Detection Using Wavelet Theory
IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, 2018Co-Authors: Khaled Al Jaafari, Amir Negahdari, Hamid A. ToliyatAbstract:In this paper, a novel stator ground fault detection method based on Wavelet Theory is tested on a lab scale synchronous generator. The lab scale setup is used to mimic the real power generation system and to simulate the fault characteristics particularly at or near the generator neutral of large industrial generators. The experimental results prove the capability of the Wavelet algorithm in synchronous generators stator winding ground fault detection.
Kit Yan Chan - One of the best experts on this subject based on the ideXlab platform.
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a new hybrid particle swarm optimization with Wavelet Theory based mutation operation
Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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IEEE Congress on Evolutionary Computation - A new hybrid Particle Swarm Optimization with Wavelet Theory based mutation operation
2007 IEEE Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
C W Yeung - One of the best experts on this subject based on the ideXlab platform.
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a new hybrid particle swarm optimization with Wavelet Theory based mutation operation
Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
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IEEE Congress on Evolutionary Computation - A new hybrid Particle Swarm Optimization with Wavelet Theory based mutation operation
2007 IEEE Congress on Evolutionary Computation, 2007Co-Authors: Sai Ho Ling, C W Yeung, Kit Yan Chan, F H F LeungAbstract:An improved hybrid particle swarm optimization (PSO) that incorporates a Wavelet-based mutation operation is proposed. It applies Wavelet Theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.
