A carregar...
Publicação
Probabilistic fuzzy clustering algorithm for fuzzy rules decomposition
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 41.48 KB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
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.
Descrição
Palavras-chave
Fuzzy clustering
Contexto Educativo
Citação
Salgado, Paulo; Igrejas, Getúlio (2007). Probabilistic fuzzy clustering algorithm for fuzzy rules decomposition. In RECPAD - 13º Conferência Portuguesa de Reconhecimento de Padrões. Lisboa