Accuracy and Similarity-Based VIKOR - TOPSIS Approach under Single-Valued Neutrosophic Linguistic Information with Applications in Antibiotic Decision-Making
摘要
In the Single-valued Neutrosophic set theory, the role of information measures as well as knowledge measures is significant. The major aim of this research paper is to investigate information and knowledge measures of the SvN-set with applications to solve decision-making (DM) issues. This paper presents knowledge measure for SvN-sets, regarding the inadequacy of existing measures. The efficacy and consistency of the proposed knowledge measure are demonstrated by taking a comparison with the current information and knowledge measures in the SvN context. We propose a similarity and a dissimilarity measure in the SvN context. Besides this, we derived an accuracy measure for SvN-sets from the proposed knowledge measure. The utilization of proposed accuracy and similarity/dissimilarity measures is given in pattern detection issues. Their efficacy is checked by taking numerical examples. A decision-making approach is then proposed by combining the VIKOR and TOPSIS approaches in the SvN context. Finally, a urinary tract infections case study is given for selecting the best antibiotic. The suggested approach’s efficacy is proved by comparing it with the existing approaches.