Construction of New Similarity Measures for Complex Pythagorean Fuzzy Sets and Their Applications in Decision-Making Problems

Abstract

Complex Pythagorean fuzzy sets (CPFSs) extend Pythagorean fuzzy sets by expressing membership, non-membership, and hesitancy degrees using complex numbers. An urgent issue in CPFSs is determining how to accurately measure the similarity between sets. Similarity measures are crucial for assessing the closeness between two objects and are extensively applied in decision-making. In this paper, we propose new similarity measures based on trigonometric functions and their weighted representations. Additionally, we investigate the properties these measures satisfy and demonstrate their effectiveness through several numerical examples. Lastly, we apply these similarity measures to decision-making problems, including pattern recognition and medical diagnosis.