Generalized Parametric Intuitionistic Fuzzy Measures Based on Trigonometric Functions for Improved Decision-Making Problem

Information theory is the study of collecting, storing, and sharing digital information. It is a nexus of disciplines such as statistics, computer science, statistical mechanics, and probability theory. This study pertains to intuitionistic fuzzy sets theory, which is a substantial component of fuzzy set theory. Nonetheless, the motive of the study is to find vague information intuitionistic fuzzy entropy measures. The authors are extend the parametric intuitionistic fuzzy entropy measures by using trigonometric functions and investigate the difference between proposed study & existing entropy measures. Furthermore, discuss the significance analysis and authenticity of the proposed study. It concludes that the proposed measure could be a good perspective for decision-making problems. Using a suitable illustration, the applicability of the proposed study has been demonstrated. Depict the graph of proposed and existing entropy measure together with their average measure. Additionally, these estimations enhance the study of information theory and produce superior information.