Parameters Optimization based on Entropy Weight and Triangular Fuzzy Number

Abstract In the present paper we discussed the parameters optimization in medical decision making using maximum entropy weight. Currently, most medical decision models rely on point estimates for input parameters, although the uncertainty surrounding these values is well-recognized. However, it still left some challenge problems that are commonly involved in computational problems involving experts’ epistemic uncertainty. This paper has motivated by existence of parameters uncertainty in the fuzzy Bayesian decision process. In addition, we examined the fuzzy entropy weight operators in two ways: through the fuzziness of the prior moments and through the fuzziness of failure data set. Advance in numerical methods and computation have made it possible to implement fuzzy Bayesian analysis in way previously research and thereby provides guidelines for decision-making and furnishes decision makers with valuable support for making reliable and robust decisions.