Algorithm

Discrete mathematics

Data mining

Computer science

Fuzzy set

Distance measures

Mathematics

Political science

Fuzzy logic

Group decision-making

Artificial intelligence

Geometry

Measure (data warehouse)

Point (geometry)

Applied Soft Computing

Intuitionistic fuzzy sets (IFSs) are successful to handle the uncertain situations of data. Distance measures of IFSs are important in the evaluation of IFSs relationships. In this paper, we analyzed the disadvantages of existing distance measures of IFSs and proposed a new distance measure called H-max of IFSs. We continued to point out some new results on intuitionistic t-norms and intuitionistic t-conorms and evaluated distance measure between two IFSs which are basically structured from these operations. Further, we combined the classification of t-representable intuitionistic fuzzy t-norms and t-conorms with the proposed distance measure to study some interesting properties. Moreover, we studied De Morgan triplets of IFSs based on the proposed distance measure. Finally, we applied the proposed distance measure to medical diagnosis problem examples and experimental validation on real-world datasets to check the applicability and effectiveness.

H-max distance measure of intuitionistic fuzzy sets in decision making