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Probabilistic clustering algorithms for fuzzy rules decomposition

dc.contributor.authorSalgado, Paulo
dc.contributor.authorIgrejas, Getúlio
dc.date.accessioned2010-11-09T15:51:46Z
dc.date.available2010-11-09T15:51:46Z
dc.date.issued2007
dc.description.abstractThe fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering and is generally applied to well defined set of data. In this paper a generalized Probabilistic fuzzy c-means (FCM) algorithm is proposed and applied to clustering fuzzy sets. This technique leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. When applied to the clustering of a flat fuzzy system results a set of decomposed sub-systems that will be conveniently linked into a Parallel Collaborative Structures.por
dc.identifier.citationSalgado, Paulo; Igrejas, Getúlio (2007). Probabilistic clustering algorithms for fuzzy rules decomposition. In Workshop on advanced fuzzy and neural control. Valenciennespor
dc.identifier.urihttp://hdl.handle.net/10198/2756
dc.language.isoengpor
dc.subjectClustering algorithmspor
dc.subjectFuzzy c-meanpor
dc.subjectFuzzy systemspor
dc.subjectRelevancepor
dc.titleProbabilistic clustering algorithms for fuzzy rules decompositionpor
dc.typeconference paper
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Orçamento de Funcionamento%2FPOSC/POSI%2FSRI%2F41975%2F2001/PT
oaire.citation.conferencePlaceValenciennespor
oaire.citation.titleWorkshop on advanced fuzzy and neural controlpor
oaire.fundingStreamOrçamento de Funcionamento/POSC
person.familyNameIgrejas
person.givenNameGetúlio
person.identifier.orcid0000-0002-6820-8858
person.identifier.ridM-8571-2013
person.identifier.scopus-author-id47761255900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublicationab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isAuthorOfPublication.latestForDiscoveryab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isProjectOfPublication154760fe-aeaf-4771-88e0-55ec65fc7d00
relation.isProjectOfPublication.latestForDiscovery154760fe-aeaf-4771-88e0-55ec65fc7d00

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