Fermatean Fuzzy Similarity Measures-Based Group Decision-Making Algorithm and Its Application to Dengue Disease

The Fermatean fuzzy set (FFS) is an effective and robust technique for handling ambiguity, to deal with issues that can’t be resolved using the concepts of Intuitionistic fuzzy set and Pythagorean fuzzy set. Due to its essential uses and crucial significance in solving insoluble real-world problems in a variety of sectors, FFS has generated a maze of research since its inception. In this elaborative study, we establish a clear definition for the concept of similarity measures along with their essential qualities in the context of FFS. Additionally, we introduced a group decision-making algorithm grounded in the suggested similarity measures to tackle the issues. The attribute weights are determined by utilizing the newly introduced similarity measures as part of the process. The credibility of the algorithm is demonstrated through a case of dengue diseases and a comparison of its results with some of the existing studies.