Building a fuzzy model with transparent membership functions through constrained evolutionary optimization

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dc.contributor.authorKim, MSko
dc.contributor.authorKim, CHko
dc.contributor.authorLee, Ju-Jangko
dc.date.accessioned2009-02-09T06:09:56Z-
dc.date.available2009-02-09T06:09:56Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2004-09-
dc.identifier.citationINTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, v.2, pp.298 - 309-
dc.identifier.issn1598-6446-
dc.identifier.urihttp://hdl.handle.net/10203/8422-
dc.description.abstractIn this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherINST CONTROL ROBOTICS & SYSTEMS-
dc.subjectSYSTEMS-
dc.subjectINTERPRETABILITY-
dc.subjectCOMPLEXITY-
dc.titleBuilding a fuzzy model with transparent membership functions through constrained evolutionary optimization-
dc.typeArticle-
dc.publisher.alternative제어로봇시스템학회en
dc.identifier.wosid000226162300004-
dc.identifier.scopusid2-s2.0-4544306325-
dc.type.rimsART-
dc.citation.volume2-
dc.citation.beginningpage298-
dc.citation.endingpage309-
dc.citation.publicationnameINTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorLee, Ju-Jang-
dc.contributor.nonIdAuthorKim, MS-
dc.contributor.nonIdAuthorKim, CH-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorEvolutionary algorithm-
dc.subject.keywordAuthormodel interpretability-
dc.subject.keywordAuthorTakagi-Sugeno-Kang fuzzy model-
dc.subject.keywordAuthortime series prediction-
dc.subject.keywordPlusSYSTEMS-
dc.subject.keywordPlusINTERPRETABILITY-
dc.subject.keywordPlusCOMPLEXITY-
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