NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM

NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM. PATTERN RECOGNITION, 27. pp. 421-428.

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Abstract

Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. An empirical study of their convergence behavior is discussed. The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. Experimental results show that the new algorithms are faster and lead to computational savings.

Item Type: Article
Subjects: Computer
Department: College of Computing and Mathematics > lndustrial and Systems Engineering
Depositing User: SHAIKH ARIFUSALAM
Date Deposited: 14 Jun 2008 10:35
Last Modified: 01 Nov 2019 13:44
URI: https://eprints.kfupm.edu.sa/id/eprint/2559