The novel concept of spherical fuzzy set consists of positive, neutral and negative membership grades which satisfy the conditions that the square sum of its membership grades is less than or equal to 1. In this paper, we investigate the family of novel similarity measures between spherical fuzzy sets based on cosine function by considering the positive, neutral, negative and refusal grades in SFSs. To implement the proposed similarity measures, we provide some numerical applications of decision-making problems. A comparative study of the proposed and existing similarity measures is established. The proposed method is more advance as compare to the previous all reflexive.
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