摘要
传统的Pawlak粗集理论对处理不完全信息系统具有一定的局限性,研究其相关理论及方法具有重大意义.本文引入随机模糊集概念,首先根据专家的领域知识对不完全信息系统进行模糊值完备化,在对象论域构造以随机模糊集为基础的复合模糊关系,以此作为构造复合近似粗糙集模型的出发点.将Krysckiewcz容差关系粗集模型和Stefanowki不对称相似关系粗集模型扩展到模糊领域,并对属性约简的一些重要概念进行模糊集扩展.本文的结果为利用粗糙集理论处理不完全信息系统提供了一种新思路.
The traditional Pawlak rough set theory has some limitations in treatment of the incomplete information systems, therefore, it is of great importance to study its related theories and methods. A fuzzy-values completion method of incomplete information systems is proposed according to the expert professional knowledge. Two kinds of composite fuzzy relations based on the random fuzzy set are constructed in objects universe, which is a starting point of construction of the composition rough set model. The Krysckiewcz rough set model and the Stefanowki rough set model are generalized to the fuzzy case, and some related important concepts are extended accordingly as well. The results provide a way for the rough set theory to utilize the incomplete information systems.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2009年第1期53-59,共7页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金资助项目(No.60474072)
关键词
粗糙集
随机模糊集
不完全信息系统
属性约简
Rough Set, Random Fuzzy Set, Incomplete Information System, Attribute Reduction
