An Intuitionistic Fuzzy Version of Hellinger Distance Measure and Its Application to Decision-Making Process

Intuitionistic fuzzy sets (IFSs), as a representative variant of sets, has substantial advantages in managing and modeling uncertain information, so it been widely studied applied. Nevertheless, how to perfectly measure the similarities or differences between IFSs is still an open question. The distance metric offers elegant desirable solution such Hence, this paper, we propose new measure, named DIFS, inspired by Hellinger probability distribution space. First, provide formal definition IFSs, analyze outstanding properties axioms satisfied which means can difference well. Besides, on basis further present normalized denoted DIFS˜. Moreover, numerical examples verify that DIFS˜ obtain more reasonable superior results. Finally, develop decision-making method top evaluate its performance two applications.