New Algorithm of Similarity Measures for Pattern-Recognition Problems

Similarity measures under intuitionistic fuzzy sets (IFSs) have received great attention because of their wide range of applications in various areas, especially in solving pattern-recognition problems. Whereas many studies have focused on proposing new similarity measures, these studies did not provide any proof that their proposed similarity measures can solve pattern-recognition problems without a tie. In this study, we propose two similarity measures and prove that these similarity measures are well defined. Furthermore, we construct an algorithm based on our proposed similarity measures and prove that our proposed algorithm can solve pattern-recognition problems under an intuitionistic fuzzy sets environment without an unsolved dilemma.