Trigonometric fuzzy entropic models and their applications towards maximum entropy principle

Abstract

There exist both types of uncertainties, viz. probabilistic as well as fuzzy but both types of uncertainties are poles apart but participate with a crucial responsibility towards reduction in uncertainties and consequently making the system under study more proficient. It has also been realized that the principle of maximum entropy plays an imperative responsibility for the study of optimization problems associated with the theoretical information measures. We have generated two new trigonometric entropic models for discrete fuzzy distributions and applied them for the knowledge of maximum entropy principle under a set of fuzzy constraints.