Memetic algorithm based fuzzy clustering

Anh Duc Do, Siu Yeung Cho

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a Memetic Algorithm (MA) based Fuzzy C-Means (FCM) clustering algorithm. Traditional FCM algorithm suffers from the problem of local optimal, whereas the proposed MA-based FCM algorithm is able to overcome this problem and produce good performance in various ways. Experimental results showed that the proposed clustering algorithm outperforms traditional fuzzy clustering algorithms significantly on a wide variety of datasets with overlapping class boundaries and spread data distributions.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages2398-2404
Number of pages7
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: 25 Sep 200728 Sep 2007

Publication series

Name2007 IEEE Congress on Evolutionary Computation, CEC 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
Country/TerritorySingapore
Period25/09/0728/09/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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