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dc.contributor.authorSeo, KK-
dc.contributor.authorPark, JH-
dc.date.accessioned2024-01-21T06:03:14Z-
dc.date.available2024-01-21T06:03:14Z-
dc.date.created2021-09-05-
dc.date.issued2004-12-
dc.identifier.issn1226-4865-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/137000-
dc.description.abstractThe recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end-of-life phase. Disposal products have the uncertainties of product status by usage influences during product use phase, and recycling cells are formed design, process and usage attributes. In order to deal with the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. Fuzzy C-mean algorithm and a heuristic approach based on fuzzy ART neural network is suggested. Especially, the modified Fuzzy ART neural network is shown that it has a good clustering results and gives an extension for systematically generating alternative solutions in the recycling cell formation problem. Disposal refridgerators are shown as examples.-
dc.languageEnglish-
dc.publisherKOREAN SOC MECHANICAL ENGINEERS-
dc.titleAdaptive clustering algorithm for recycling cell formation: An application of fuzzy ART neural networks-
dc.typeArticle-
dc.identifier.doi10.1007/BF02990218-
dc.description.journalClass1-
dc.identifier.bibliographicCitationKSME INTERNATIONAL JOURNAL, v.18, no.12, pp.2137 - 2147-
dc.citation.titleKSME INTERNATIONAL JOURNAL-
dc.citation.volume18-
dc.citation.number12-
dc.citation.startPage2137-
dc.citation.endPage2147-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000225586200007-
dc.identifier.scopusid2-s2.0-15844365835-
dc.relation.journalWebOfScienceCategoryEngineering, Mechanical-
dc.relation.journalResearchAreaEngineering-
dc.type.docTypeArticle-
dc.subject.keywordAuthorfuzzy theory-
dc.subject.keywordAuthorfuzzy C-mean algorithm-
dc.subject.keywordAuthorfuzzy ART neural network-
dc.subject.keywordAuthorrecycling cell formation-
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KIST Article > 2004
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