基于加权信息熵的直觉模糊信息系统的三支决策

讨论直觉模糊信息系统上的三支决策问题.首先,定义一个由模糊因子、均值因子和概率因子3部分组成的相似度函数,从而建立直觉模糊信息系统上的三支决策模型,并指出该模型从理论上统一了各种双论域模型;其次,考虑论域对象的评价值不同,提出一种基于评价值的划分测度:加权信息熵,并且证明划分越细,加权信息熵越大;最后,基于加权信息熵的性质,给出最优三划分的合理解释,从而提出一种新的阈值求解方法.

Three-way decision of intuitionistic fuzzy information systems based on the weighted information entropy

This paper discusses three-way decision problems on intuitionistic fuzzy information systems. Firstly, a similarity degree function is defined, which is composed of the fuzzy factor, the mean factor and the probability factor, and then a three-way decision model on intuitionistic fuzzy information systems is established, and it is pointed out that the model theoretically unifies all kinds of two-universe models. Secondly, considering the different evaluation values of objects in the universe, this paper proposes a partition measure based on evaluation values: the weighted information entropy, and it is proved that the finer the partition is, the greater the weighted information entropy is. Finally, based on the property of the weighted information entropy, a reasonable explanation of the optimal tri-partition is given, and a new thresholds solution method is proposed.