Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/890
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dc.contributorDepartment of Electrical Engineering-
dc.creatorYang, S-
dc.creatorMachado, JM-
dc.creatorNi, G-
dc.creatorHo, SL-
dc.creatorZhou, P-
dc.date.accessioned2014-12-11T08:28:33Z-
dc.date.available2014-12-11T08:28:33Z-
dc.identifier.issn0018-9464-
dc.identifier.urihttp://hdl.handle.net/10397/890-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2000 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.subjectDomain elimination methoden_US
dc.subjectGlobal optimizationen_US
dc.subjectSelf-learning abilityen_US
dc.subjectSimulated annealing algorithmen_US
dc.titleA self-learning simulated annealing algorithm for global optimizations of electromagnetic devicesen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: S. L. Hoen_US
dc.identifier.spage1004-
dc.identifier.epage1008-
dc.identifier.volume36-
dc.identifier.issue4-
dc.identifier.doi10.1109/20.877611-
dcterms.abstractA self-learning simulated annealing algorithm is developed by combining the characteristics of simulated annealing and domain elimination methods. The algorithm is validated by using a standard mathematical function and by optimizing the end region of a practical power transformer. The numerical results show that the CPU time required by the proposed method is about one third of that using conventional simulated annealing algorithm.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on magnetics, July 2000, v. 36, no. 4, p. 1004-1008-
dcterms.isPartOfIEEE transactions on magnetics-
dcterms.issued2000-07-
dc.identifier.isiWOS:000090067900084-
dc.identifier.scopus2-s2.0-0034217702-
dc.identifier.eissn1941-0069-
dc.identifier.rosgroupidr02775-
dc.description.ros2000-2001 > 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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