Multi-Criteria Decision-Making Approach Based on Correlation Coefficient for Multi-Polar Interval-Valued Neutrosophic Soft Set

Abstract

The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantly generalized version of m-polar neutrosophic soft sets and serves as a substantial extension of interval-valued neutrosophic soft sets. In this scenario, we delineate the correlation coefficient (CC) and the weighted correlation coefficient (WCC), together with their pertinent features, specifically designed for mPIVNSSs. A multi-criteria decision-making (MCDM) technique has been established based on the proposed correlation measures. To demonstrate the efficacy and relevance of the MCDM method, we present a detailed mathematical illustration. The study emphasizes the utility, impact, and flexibility of the created method through comparison analysis with traditional methodologies, illustrating its efficacy in resolving complicated decision-making situations.