ADVANCES IN INTELLIGENT DATA ANALYSIS, cilt.1280, ss.383-393, 1997 (SCI İndekslerine Giren Dergi)
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.