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Clustering algorithms for fuzzy rules decomposition

dc.contributor.authorSalgado, Paulo
dc.contributor.authorIgrejas, GetĂșlio
dc.date.accessioned2010-11-09T15:54:13Z
dc.date.available2010-11-09T15:54:13Z
dc.date.issued2007
dc.description.abstractThis paper presents the development, testing and evaluation of generalized Possibilistic fuzzy c-means (FCM) algorithms applied to fuzzy sets. Clustering is formulated as a constrained minimization problem, whose solution depends on the constraints imposed on the membership function of the cluster and on the relevance measure of the fuzzy rules. This fuzzy clustering of fuzzy rules 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 Hierarchical Prioritized Structures.por
dc.identifier.citationSalgado, Paulo; Igrejas, GetĂșlio (2007). Clustering algorithms for fuzzy rules decomposition. In Proceedings of the UK Computational Intelligence Workshop. Londonpor
dc.identifier.urihttp://hdl.handle.net/10198/2757
dc.language.isoengpor
dc.subjectFuzzy clusteringpor
dc.subjectRules decompositionpor
dc.titleClustering algorithms for fuzzy rules decompositionpor
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Orçamento de Funcionamento%2FPOSC/POSI%2FSRI%2F41975%2F2001/PT
oaire.citation.conferencePlaceLondonpor
oaire.citation.titleProceedings of the UK Computational Intelligence Workshoppor
oaire.fundingStreamOrçamento de Funcionamento/POSC
person.familyNameIgrejas
person.givenNameGetĂșlio
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 CiĂȘncia 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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