Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/882
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dc.contributorDepartment of Electrical Engineering-
dc.contributorIndustrial Centre-
dc.creatorYang, S-
dc.creatorHo, SL-
dc.creatorNi, G-
dc.creatorWong, HCC-
dc.date.accessioned2014-12-11T08:25:16Z-
dc.date.available2014-12-11T08:25:16Z-
dc.identifier.issn0018-9464-
dc.identifier.urihttp://hdl.handle.net/10397/882-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2005 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.subjectDynamic-Q methoden_US
dc.subjectGlobal optimizationen_US
dc.subjectOptimal designen_US
dc.subjectResponse surface methodologyen_US
dc.titleAn adaptive optimal strategy based on the combination of the dynamic-Q optimization method and response surface methodologyen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: S. L. Hoen_US
dc.description.otherinformationAuthor name used in this publication: H. C. Wongen_US
dc.identifier.spage1760-
dc.identifier.epage1763-
dc.identifier.volume41-
dc.identifier.issue5-
dc.identifier.doi10.1109/TMAG.2005.846031-
dcterms.abstractThe dynamic-Q optimization method is combined with an interpolating moving least-squares approximation-based response surface model to design an efficient adaptive strategy for solving computationally heavy design problems. The proposed optimal strategy is validated by comparing its performances in finding the solutions of other common optimal methods on two different kinds of problems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on magnetics, May 2005, v. 41, no. 5, p. 1760-1763-
dcterms.isPartOfIEEE transactions on magnetics-
dcterms.issued2005-05-
dc.identifier.isiWOS:000229084200102-
dc.identifier.scopus2-s2.0-22044432784-
dc.identifier.eissn1941-0069-
dc.identifier.rosgroupidr20902-
dc.description.ros2004-2005 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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