A new Interval Type-2 Fuzzy Possibilistic C-Means clustering algorithm

Abstract

In this paper we are presenting the extension of the Fuzzy Possibilistic C-Means (FPCM) algorithm using Type-2 Fuzzy Logic techniques, with the goal of improving the performance of this algorithm. We also performed the comparison of this proposed algorithm against the Interval Type-2 Fuzzy C-means (IT2FCM) algorithm to observe if the proposed approach performs better than this algorithm. The proposed extension was realized considering both of the weight exponents (fuzzy and possibilistic) the m and η as interval fuzzy sets.