Genetic fuzzy clustering by means of discovering membership functions

Turhan M.

ADVANCES IN INTELLIGENT DATA ANALYSIS, cilt.1280, ss.383-393, 1997 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 1280
  • Basım Tarihi: 1997
  • Dergi Adı: ADVANCES IN INTELLIGENT DATA ANALYSIS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.383-393
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

It has been observed that in the previous Genetic Algorithms (GA) based Fuzzy Clustering (FC) works only some of the parameters of an FC system are developed. Here, a new approach is proposed to develop directly the membership functions for the clusters using GA. This new technique is implemented and tested on common test data. A comparative study of the results against the quotations in literature reveals that the standard c-means FC technique is outperformed by the proposed technique in the count of misclassifications aspect.