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|Title:||Probabilistic fuzzy clustering algorithm for fuzzy rules decomposition|
|Citation:||Salgado, Paulo; Igrejas, Getúlio (2007) - Probabilistic fuzzy clustering algorithm for fuzzy rules decomposition. In RECPAD - 13º Conferência Portuguesa de Reconhecimento de Padrões. Lisboa|
|Abstract:||The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy clustering and is generally applied to well defined sets of data. In this work a generalized Probabilistic Fuzzy C-Means (PFCM) algorithm is proposed and applied to fuzzy sets clustering. The methodology presented 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 the result is a set of decomposed sub-systems that will be conveniently linked into a Parallel Collaborative Structure.|
|Appears in Collections:||DE - Artigos em Proceedings Não Indexados ao ISI/Scopus|
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