A new approach to the problem of clustering using the fuzzy joint points method

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dc.contributor.authorNasibov E.N.
dc.contributor.authorUlutagay G.
dc.date.accessioned2019-10-27T00:10:04Z
dc.date.available2019-10-27T00:10:04Z
dc.date.issued2005
dc.departmentEge Üniversitesien_US
dc.description.abstractA new hierarchical approach to the problem of clustering, called the Fuzzy Joint Point, FJP) method is proposed. In the FJP method each element of the clusterized set is considered a fuzzy point of a multidimensional space. The concepts of a fuzzy conical point, fuzzy ?-neighborhood, and fuzzy ?-joint points are introduced and studies of certain properties relative to these concepts are carried out. The proposed algorithm of the FJP method may be used as a preparatory stage of the Fuzzy c-Means (FCM) algorithm for determining the initial classes and their dimensions and also as an independent clustering algorithm. © 2006 by Allerton Press, Inc.en_US
dc.identifier.endpage17en_US
dc.identifier.issn0146-4116
dc.identifier.issn0146-4116en_US
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage8en_US
dc.identifier.urihttps://hdl.handle.net/11454/21862
dc.identifier.volume39en_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 conical pointen_US
dc.subjectFuzzy joint points (FJP)en_US
dc.subjectFuzzy joint seten_US
dc.titleA new approach to the problem of clustering using the fuzzy joint points methoden_US
dc.typeArticleen_US

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