Picture fuzzy set is an efficient tool to realize the content of vagueness and uncertainty specifically in circumstances that could not be easily handled by intuitionistic fuzzy sets such as human voting, personnel selection, medical diagnosis, etc. The analysis showed that the suggested methodology is reliable, flexible, and consistent with the existing techniques. Finally, we establish the comparative study of our developed measures over the existing correlation coefficient measures. The aim of this study is to propose a novel and efficient methodology for evaluation of supplier’s selection with uncertain information.
Using numerical computations, we determine the efficacy of the suggested measures over other measures. With the help of proposed correlation coefficient, we establish some weighted measures for FFS. As there does not exist any study concerning correlation coefficient measures for FFS, in this communication, we propose novel entropy-correlation measures for Fermatean fuzzy sets and applied it decision making problems of pattern analysis and multi-criteria decision making for supplier selection. Keeping in mind the importance of correlation coefficient and application in medical diagnosis, decision making and pattern recognition, several studies on correlation coefficient measures have been proposed in the literature.
Fermatean fuzzy set (FFS) is an effective tool to depict expert reasoning information in the decision‐making process than fuzzy sets (FS), intuitionistic fuzzy sets (IFS), and Pythagorean fuzzy sets (PFS).
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