Maximum Entropy Functions of Discrete Fuzzy Random Variables

Lianlong Gao, Liang Lin, Ling Gao

Abstract


Due to deficiency of information, the probability distribution and membership functions of a fuzzy random variable
cannot be obtained explicitly. It is a challenging work to find an appropriate probability distribution and membership
function when certain partial information about a fuzzy random variable is given, such as expected value or moments.
This paper solves such problems for the maximum entropy of discrete fuzzy random variables with certain constraints. A
genetic algorithm is designed to solve the general maximum entropy model for discrete fuzzy random variables, which is
illustrated by numerical experiment.

Full Text: PDF DOI: 10.5539/jmr.v2n3p78

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Journal of Mathematics Research   ISSN 1916-9795 (Print)   ISSN 1916-9809 (Online)

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