Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1448
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Electronic and Information Engineering-
dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorLing, SH-
dc.creatorIu, HHC-
dc.creatorChan, KY-
dc.creatorLam, HK-
dc.creatorYeung, BCW-
dc.creatorLeung, FHF-
dc.date.accessioned2014-12-11T08:24:40Z-
dc.date.available2014-12-11T08:24:40Z-
dc.identifier.issn1083-4419-
dc.identifier.urihttp://hdl.handle.net/10397/1448-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2008 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.en_US
dc.rightsThis 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.en_US
dc.subjectLoad flow problemen_US
dc.subjectModelingen_US
dc.subjectMutation operationen_US
dc.subjectNeural network controlen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectWavelet theoryen_US
dc.titleHybrid particle swarm optimization with wavelet mutation and its industrial applicationsen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: H. H. C. Iuen_US
dc.description.otherinformationAuthor name used in this publication: Frank H. Leungen_US
dc.description.otherinformationCentre for Multimedia Signal Processing, Department of Electronic and Information Engineeringen_US
dc.identifier.spage743-
dc.identifier.epage763-
dc.identifier.volume38-
dc.identifier.issue3-
dc.identifier.doi10.1109/TSMCB.2008.921005-
dcterms.abstractA new hybrid particle swarm optimization (PSO) that incorporates a wavelet-theory-based mutation operation is proposed. It applies the wavelet theory to enhance the PSO in exploring the solution space more effectively for a better solution. A suite of benchmark test functions and three industrial applications (solving the load flow problems, modeling the development of fluid dispensing for electronic packaging, and designing a neural-network-based controller) are employed to evaluate the performance and the applicability of the proposed method. Experimental results empirically show that the proposed method significantly outperforms the existing methods in terms of convergence speed, solution quality, and solution stability.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on systems, man, and cybernetics. Part B, Cybernetics, June 2008, v. 38, no. 3, p. 743-763-
dcterms.isPartOfIEEE transactions on systems, man, and cybernetics. Part B, Cybernetics-
dcterms.issued2008-06-
dc.identifier.isiWOS:000258763600014-
dc.identifier.scopus2-s2.0-44849086452-
dc.identifier.rosgroupidr37111-
dc.description.ros2007-2008 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Hybrid particle swarm optimization_08.pdf2.22 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

111
Last Week
1
Last month
Citations as of Mar 24, 2024

Downloads

259
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

248
Last Week
1
Last month
2
Citations as of Mar 28, 2024

WEB OF SCIENCETM
Citations

201
Last Week
0
Last month
3
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


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