A Novel Spherical Fuzzy VIKOR Approach Based on TODIM for Evaluating and Ranking the Opinion Polls With Shannon Entropy and Jensen-Shannon Divergence Measure

Abstract

Based on traditional VIKOR (VlseKriterijumska Optimizacija IKompromisno Resenje) method of MCDM (Multi-criteria decision making), the compromised solution presented in this article offers a fresh viewpoint and can control the psychological behaviour of decision makers by causing TODIM (a Portuguese acronym meaning Interactive Multi-Criteria Decision Making). In order to set the criteria weights in advance, the accuracy and mathematical merits of the suggested measures are discussed by describing Spherical Fuzzy Entropy and Jensen-Shannon Divergence measures. Spherical fuzzy sets (SFSs) have lately gained popularity across a number of disciplines. It has numerous critical application domains, including pattern recognition, data mining, decision making, and medical diagnosis. Several other information measures of SFSs have been proposed in the little time since their initial appearance, but the literature has only covered a small portion of them. This paper presents several innovative information metrics for spherical fuzzy collections. Finally, the proposed method of using opinion surveys to predict election results is demonstrated numerically, and the results are fairly compared to other MCDM techniques that are already documented in the literature. Successful experiment findings are also attained.

Keywords

• Divergence
• entropy
• spherical fuzzy set
• TODIM
• VIKOR