A spherical fuzzy knowledge measure with its application in the identification of the best hazardous waste transportation firm

Fuzzy logic is an excellent way to deal with the inherent unpredictability and ambiguity in making judgments, and the idea of spherical fuzzy sets is one of the most recent advancements in this field. Since the squared total of membership, non-membership, and hesitation degrees should be between 0 and 1 and each degree should be defined in [0, 1], the hesitation of the decision-maker(s) about an attribute can be conveyed more thoroughly. In this study, we suggest a spherical fuzzy knowledge measurement and demonstrate its capacity to satisfy the axiomatic requirements. We compared it with all the existing spherical fuzzy information metrics through various aspects such as ambiguity computation, linguistic hedges, and attribute weight computation. Based on the proposed knowledge metric, we introduce the Complex Proportional Assessment (COPRAS) method for spherical fuzzy sets and illustrate it with a numerical example concerning the selection of the best hazardous waste transportation firm.