A novel intuitionistic Renyi’s–Tsallis discriminant information measure and its applications in decision-making

Abstract

The intuitionistic fuzzy sets are an important way to express uncertain information, and they are superior to the fuzzy sets. In this paper, we propose a new measure of intuitionistic fuzzy sets along with various properties. The new intuitionistic Renyi’s–Tsallis discriminant information measure has some desirable merits, in which it meets the distance measurement axiom and can better indicate the discrimination degree of IFSs. Then further, the idea has been generalized from fuzzy sets to well-known novel intuitionistic discriminant information measure. Some of the major properties are discussed to show the effectiveness of our proposed divergence measure. A comparison study is conducted to illustrate the validity and superiority of the proposed discriminant measure. The proposed measure is utilized to calculate the degree of discrimination between intuitionistic fuzzy sets. Finally, some practical examples are employed in the field of medical diagnosis and pattern recognition. In this paper, we also propose an algorithm for pattern recognition using proposed discriminant information measure. This algorithm is demonstrated by some examples and outcome is compared with other existing methods.