Dynamic Similarity Measures between Intuitionistic Fuzzy Sets and Its Application

Although many measures of similarity between intuitionistic fuzzy set (IFS) have been proposed in the literature, some existing similarity measures are not always effective in some cases. A main reason is that existing similarity measures have not or little considered degree of hesitancy in intuitionistic fuzzy set. In this paper, based on this foundation that the degree of hesitancy in intuitionistic fuzzy set and decision maker's attitude to indetermination information are taken into account, a dynamic similarity measure is proposed for measuring the degree of similarity between IFSs. To demonstrate the efficiency of the proposed dynamic similarity measures, the existing similarity measures between IFSs are compared with the dynamic similarity measure between IFSs by numerical examples. It is shown that the proposed similarity measures can deal with counter-intuitive cases more effectively and reasonably than some existing methods. Finally, dynamic similarity measure is applied to pattern recognition.