In this paper, we defined ten similarity measures between spherical fuzzy sets (SFSs) based on the cosine function by considering the degree of positive-membership, degree of neutral-membership, degree of non-membership and degree of refusual-membership in SFSs. Then, we applied these similarity measures and weighted similarity measures between SFSs to pattern recognition and medical diagnosis. Finally, two illustrative examples are designed to show the efficiency of the similarity measures for pattern recognition and medical diagnosis.
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Wei et al. (2019) studied this question.
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