The behavior of particles in the Particle Swarm Clustering algorithm
Tipo
Artigo de evento
Data de publicação
2010
Periódico
2010 IEEE World Congress on Computational Intelligence, WCCI 2010
Citações (Scopus)
4
Autores
Szabo A.
Prior A.K.F.
De Castro L.N.
Prior A.K.F.
De Castro L.N.
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Resumo
The Particle Swarm Clustering (PSC) algorithm uses collective intelligence to solve clustering problems. It simulates the interaction of individuals, which use their own experience (cognitive term), social experience (social term) and interaction with the environment (self-organizing term) to cluster objects in different groups. In this work a study of the behavior of particles and an analysis of the PSC convergence were performed considering each term that composes the particles' adaptation equation. The objective was to evaluate the relevance of each of these terms within the context of clustering data. © 2010 IEEE.
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Assuntos Scopus
Clustering data , Clustering problems , Collective intelligences , Particle swarm , Self organizing