Trigonometric Divergence Measures of Intuitionistic Fuzzy Sets based on Jensen-Shannon Inequality for Solving Bacteria Detection and Decision-Making Problem
Abstract
In this present era, it is a big challenge to make a good decision in some circumstances with distinct attributes. Various authors have provided their individual decision-making methods about how to handle these circumstances and make the right decision. This study adopts to solve the multi-criteria decision-making problem and make an appropriate decision with the help of some different attributes. In this communication, we will develop two Jensen-Shannon trigonometric divergence measures for intuitionistic fuzzy sets on the conception of Jensen-Shannon inequality and axiomatically discuss the various properties. Both proposed measures are obtained by the setting of IFSs theory, and these are completely different innovative from the studies so far also different from each other. The present study is mainly furnished with the decision-making techniques included TOPSIS, MOORA, MADM and bacteria detection problem. Numerous authors have been provided their individual decision-making methods about how to handle these circumstances and make the right decision. Furthermore, with the help of a numerical example the developed divergence measures utilizing to solve the decision-making problem as well as bacteria detection problem for detect the correct bacteria based on the shape of unknown bacteria. In addition, the graphically representation of proposed and existing divergence measures by utilizing created techniques with their comparison. The representation of the proposed study will improve to solve the decision-making problems and provides the reliable decision.
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