Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP

Similarity measure plays an important role when estimating the degree of resemblance between two sets or objects. A variety of similarity measures are suggested in the literature in the context of fuzzy sets and their generalizations, but a similarity measure of q-rung orthopair fuzzy sets (q-ROFSs) based on below, above and centre fuzzy sets has not been considered so far. Therefore, in this paper, we propose a novel similarity measure based on the information carried by transforming q-rung orthopair fuzzy sets into their below, above and centre fuzzy sets to calculate the degree of similarity between two q-ROFSs. We also construct an axiomatic definition for the proposed similarity measure of q-ROFS. Furthermore, to show the competency, reliability and applicability of our proposed similarity measure, we present several examples related to pattern recognition and multicriteria decision making. Finally, we construct an algorithm for Orthopairian Portuguese interactive and multicriteria decision making (O-TODIM) based on our proposed similarity measure between q-ROFSs, to handle complex multicriteria decision making problems related to daily life. Our demonstration shows that the proposed method is reasonable and reliable in handling different problems related to daily life settings in the q-ROFSs environment.