The proposal of a fuzzy clustering algorithm based on particle swarm

Author

Szabo, Alexandre ; de Castro, Leandro N. ; Delgado, Myriam Regattieri

Author_Institution

Natural Comput. Lab. - LCoN, Mackenzie Univ., Sao Paulo, Brazil

fYear

2011

fDate

19-21 Oct. 2011

Firstpage

459

Lastpage

465

Abstract

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.

Keywords

fuzzy set theory; particle swarm optimisation; pattern clustering; crisp data clustering algorithm; fuzzy PSO; fuzzy c-means; fuzzy particle swarm clustering algorithm; winner particle; Algorithm design and analysis; Clustering algorithms; Databases; Equations; Particle swarm optimization; Partitioning algorithms; Vectors; bioinspired algorithms; fuzzy c-means algorithm; fuzzy data clustering; particle swarm data clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on

Conference_Location

Salamanca

Print_ISBN

978-1-4577-1122-0

Type

conf

DOI

10.1109/NaBIC.2011.6089630

Filename

6089630