Escalation of Weighted Fuzzy Entropic Models and Their Applications for the Study of Maximum Entropy Principle

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Om Parkash, Rakesh Kumar

Abstract

The continued existence of mutual categories of uncertainties, viz. probabilistic and fuzzy nevertheless both are away from each other, even though contribute with a fundamental accountability in declining uncertainties and accordingly constructing the structure under learning supplementary skilled. Additionally, it is apprehended that the maximum entropy principle cooperate with a crucial accountability for the learning of optimization problems connected with the hypothetical information models. The current communication has been produced from this position of observation and formulates transaction with two new entropic models for discrete fuzzy distributions and additionally makes them functional for the acquaintance of maximum entropy principle under the situation of fuzzy constraints.

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