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Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/2757

Título: Clustering algorithms for fuzzy rules decomposition
Autor: Salgado, Paulo
Igrejas, Getúlio
Palavras-chave: Fuzzy clustering
Rules decomposition
Issue Date: 2007
Citação: Salgado, Paulo; Igrejas, Getúlio (2007) - Clustering algorithms for fuzzy rules decomposition. In Proceedings of the UK Computational Intelligence Workshop. London
Resumo: This 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.
URI: http://hdl.handle.net/10198/2757
Appears in Collections:DE - Artigos em Proceedings Não Indexados ao ISI

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