Higher order fuzzy entropy and hybrid entropy of a set
Information Sciences: an International Journal
Some new information measures for fuzzy sets
Information Sciences: an International Journal
Measures of entropy and fuzziness related to aggregation operators
Information Sciences—Intelligent Systems: An International Journal
Fuzzy sets as a basis for a theory of possibility
Fuzzy Sets and Systems
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
A survey of credibility theory
Fuzzy Optimization and Decision Making
Information Sciences: an International Journal
Is there a need for fuzzy logic?
Information Sciences: an International Journal
Computers & Mathematics with Applications
Uncertainty Theory
On the entropy of fuzzy measures
IEEE Transactions on Fuzzy Systems
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
Entropy of Credibility Distributions for Fuzzy Variables
IEEE Transactions on Fuzzy Systems
Δ-Entropy: Definition, properties and applications in system identification with quantized data
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy numbers from raw discrete data using linear regression
Information Sciences: an International Journal
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Due to the deficiency of information, the membership function of a fuzzy variable cannot be obtained explicitly. It is a challenging work to find an appropriate membership function when certain partial information about a fuzzy variable is given, such as expected value or moments. This paper solves such problems for discrete fuzzy variables via maximum entropy principle and proves some maximum entropy theorems with certain constraints. A genetic algorithm is designed to solve the general maximum entropy model for discrete fuzzy variables, which is illustrated by some numerical experiments.