摘要
粗糙集理论是一种处理不确定性问题的有力工具,它假定知识是一种对对象进行分类的能力.分类是推理、学习与决策中的关键问题.传统粗糙集所基于的是不分明关系,这往往使得分类过细,因而笔者探讨一种基于模糊相似矩阵的分类方式,把传统的等价关系弱化为模糊等价关系,从而可得到更具表达力的粗糙集模型.
Rough set as a theory of set with boundary is widely to deal with the information under uncertainty. It assumes that knowledge is a kind of capability of classification. Classification is an important problem about inference and knowledge acquisition and decision. The original rough set bases on equivalence relation, which makes the classification too detailed. So the author devotes a methodology for classification based on fuzzy similar matrix to make the mould of rough set much better. It is a generalized approach of the original equivalence relation.
出处
《太原师范学院学报（自然科学版）》
2005年第3期12-15,共4页
Journal of Taiyuan Normal University:Natural Science Edition
关键词
粗糙集
等价关系
模糊相似矩阵
Rough set
equivalence relation
fuzzy similar matrix
