A Novel Similarity Measure Based on Accuracy Score of Conventional Type of Trapezoidal-Valued Intuitionistic Fuzzy Sets and Its Applications in Multi-criteria Decision-Making Problems

Abstract The article aims to investigate the distance measure between any two conventional type trapezoidal-valued intuitionistic fuzzy sets (CTrVIFSs) whose membership and non-membership grades of an element are expressed as trapezoidal numbers (CTrIFN). Using proposed measure, similarity CTrVIFSs is determined its efficiency shown by applying it pattern recognition problems MCDM problems. propounded in this can be used tackle real-world involving CTrVIFS parameters, such clustering, machine learning, DNA matching. application section discusses that research help decision-makers recognize patterns categorize samples with those patterns. Furthermore, model a problem given which utilizes suggested solve problems, demonstrate usability new technique comprehend applied intelligence above other methods. Finally, general conclusion future scope on topic discussed.