The proposal of a fuzzy clustering algorithm based on particle swarm
Tipo
Artigo de evento
Data de publicação
2011
Periódico
Proceedings of the 2011 3rd World Congress on Nature and Biologically Inspired Computing, NaBIC 2011
Citações (Scopus)
13
Autores
Szabo A.
De Castro L.N.
Delgado M.R.
De Castro L.N.
Delgado M.R.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
This paper proposes the Fuzzy Particle Swarm Clustering (FPSC) algorithm, which is an extension of the crisp data clustering algorithm PSC particularly tailored to deal with fuzzy clusters. The main structural changes of the original PSC algorithm to design FPSC occurred in the selection and evaluation steps of the winner particle, comparing the degree of membership of each object from the database in relation to the particles in the swarm. The FPSC algorithm was applied to eight databases from the literature with the purpose of benchmarking and its performance was compared with that of Fuzzy C-Means and Fuzzy PSO. The results showed that the FPSC algorithm is competitive with the algorithms discussed in this paper. © 2011 IEEE.
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Assuntos Scopus
Bio-inspired algorithms , Crisp data , Degree of membership , Fuzzy C mean , Fuzzy C-means algorithms , Fuzzy clusters , Fuzzy data , Fuzzy particle swarm , Particle swarm , particle swarm data clustering , Structural change