Entropy Measures for Dual Hesitant Fuzzy Information

In reality, there often exist some situations with high degree of uncertainty where a decision organization consisting of several experts is not very sure about a value, but hesitant among several possible values when providing the membership degree or non-membership degree of an element to a set. In such cases, dual hesitant fuzzy sets are usually utilized to represent the assessments of the decision organization. Since entropy is a very important tool to measure the uncertainty of information, this paper investigates the entropy models on dual hesitant fuzzy information. Firstly, we introduce some axiomatic requirements that a dual hesitant fuzzy entropy measure should satisfy. Then we discuss the construction of dual hesitant fuzzy entropy measures and present several entropy formulas with the help of some simple functions. At length, an illustrative example is given to validate the practicality and effectiveness of the developed entropy measures.