On the fuzzy joint points method for the problem of fuzzy clustering

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dc.contributor.authorNasibov E.N.
dc.contributor.authorUlutagay G.
dc.date.accessioned2019-10-27T00:01:54Z
dc.date.available2019-10-27T00:01:54Z
dc.date.issued2006
dc.departmentEge Üniversitesien_US
dc.description.abstractThe present article considers the fuzzy joint points (FJP) method for the problem of fuzzy clustering. The FJP method is based on the creation of joint sets starting with use of the fuzzy neighbor relation between elements. The principal distinctive property here is the existence of a built-in mechanism of defining an optimal number of classes. However, the degree of adequacy of the number of classes depends on the structure of the data. In the present article the FJP method is investigated and a sufficient condition for correct recognition of the optimal number of classes is proved. © Allerton Press, Inc., 2006.en_US
dc.identifier.endpage31en_US
dc.identifier.issn0146-4116
dc.identifier.issn0146-4116en_US
dc.identifier.issue5en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage23en_US
dc.identifier.urihttps://hdl.handle.net/11454/21587
dc.identifier.volume40en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofAutomatic Control and Computer Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFuzzy clusteringen_US
dc.subjectFuzzy joint points (FJP)en_US
dc.subjectFuzzy joint seten_US
dc.subjectFuzzy pointen_US
dc.titleOn the fuzzy joint points method for the problem of fuzzy clusteringen_US
dc.typeArticleen_US

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