严格直觉模糊熵

通过对现有直觉模糊熵构造方法的分析,针对隶属度和非隶属度函数相等但直觉指数不同导致熵值无法区分的局限性,借鉴经典数学中严格大于和严格小于的概念,提出了严格直觉模糊熵(strict intuitionistic fuzzy entropy,SIFE)的概念并给出公理化定义。在该定义基础上给出一个SIFE构造方法,然后抽象为一般表达式,使得SIFE的特性在决策排序问题中更加适用。通过算例分析,表明该方法的正确性,与其他直觉模糊熵构造方法比较,说明该方法可以克服存在的局限性。

Strict intuitionistic fuzzy entropy

Methods of intuitionistic fuzzy entropy are analyzed. Considering the classical mathematic concepts of strict greater than and strict less than, a concept strict intuitionistic fuzzy entropy (SIFE) and an axiomatic definition are proposed by solving defect that entropy of the degree of membership function equals the degree of none membership function but different intuitionistic indexes cannot be distinguished. A technique for constructing the SIFE based on this definition is proposed and an expression is abstracted. The SIFE is more adaptive in decision and sorting. The validity is certified by the example and the limit is overcomed by comparing to other methods.