粗糙集模型的拓广

The Extension of the Rough Set Model

由于信息的不完备以及论域上的二元关系常常是不等价的,需要将经典粗糙集模型进行扩充。一方面,将粗糙集模型中等价关系泛化为容差关系或包含关系,可将粗糙集模型的适用范围扩大,在此基础上研究其上、下近似算子,并通过案例对比两种关系的差别;另一方面,从基本知识粒度的构造和知识的表示方法上,研究基于邻域系统和粒度两个方面的上、下近似算子。

Because of the incomplete information and inequivalent binary relation on the domain, the classic rough set model will need to be expanded. On the one hand, the equivalence relations of the rough set model is extended to tolerance relations or inclusion relations, which can extend the application range. This paper studies high and low approximation operators on the basis of this method and compares with the two kinds of relations through case analysis. On the other hand, on the basic of granularity of knowledge structure and knowledge representation method, it studies the approximation operators from two aspects of neighborhood system and granularity.