Comparison measures for Pythagorean m-polar fuzzy sets and their applications to robotics and movie recommender system

The perception of comparison measures is vitally significant in more or less every scientific field. They have many practical implementations in areas such as medicine, molecular biology, management, meteorology, etc. In this article, novel similarity, distance, and correlation comparison measures for Pythagorean m-polar fuzzy sets are proposed. The leading qualities of these comparison measures are investigated. The numerical examples are provided to demonstrate their formulation. In PmFSs, elements are allowed to duplicate finitely, which supports the usage of the measures put forward in here-and-now situations where we ponder time and again to reach some decision. The three algorithms are proposed to discuss the applications of comparison measures for PmFSs in robotics and movie recommender systems.

Automated summary

This article proposes novel similarity, distance, and correlation comparison measures for Pythagorean m-polar fuzzy sets, and investigates their leading qualities. Numerical examples are provided to demonstrate their formulation. In PmFSs, elements are allowed to duplicate finitely, which supports their usage in here-and-now situations where decisions are repeatedly pondered. Additionally, three algorithms are proposed to discuss the applications of comparison measures for PmFSs in robotics and movie recommender systems.