A Unified Approach to Similarity Measures Between Intuitionistic Fuzzy Sets

Two general classes of similarity measures between intuitionistic fuzzy sets (hereafter IFSs) are introduced. Some properties of these measures are investigated with respect to some well-known reasonable axioms. It is shown that several similarity measures between IFSs introduced elsewhere can be expressed by these definitions as special cases. Some illustrative and practical examples from the areas of pattern recognition, fuzzy clustering analysis, and decision making will be used to investigate the performance of the proposed measures with respect to some common measures. The results indicate that these measures can provide a useful way for measuring the degree of similarity between IFSs and that the proposed approach performs well in pattern recognition, fuzzy clustering, and decision making.