Please use this identifier to cite or link to this item:
PIRA download icon_1.1View/Download Full Text
Title: A new hybrid particle swarm optimization with wavelet theory based mutation operation
Authors: Ling, SH
Yeung, CW
Chan, KY
Leung, FHF 
Issue Date: 2007
Source: CEC 2007 : IEEE Congress on Evolutionary Computation, Singapore, 25–28 September 2007, p. 1977-1984
Abstract: 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.
Keywords: Associative storage
Convergence of numerical methods
Function evaluation
Neural networks
Quality control
Wavelet transforms
Publisher: IEEE
ISBN: 1-4244-1340-0
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
Wavelet theory based mutation_07.pdf332.12 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Last Week
Last month
Citations as of Jun 4, 2023


Citations as of Jun 4, 2023


Last Week
Last month
Citations as of Jun 8, 2023

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.