粗糙集理论中知识粗糙性与信息熵关系的讨论  

ON THE RELATIONSHIPS BETWEEN INFORMATION ENTROPY AND ROUGHNESS OF KNOWLEDGE IN ROUGH SET THEORY

作　　者：苗夺谦[1] 王珏[1] 

机构地区：[1]中国科学院自动化研究所,北京100080

出　　处：《模式识别与人工智能》1998年第1期34-40,共7页Pattern Recognition and Artificial Intelligence

摘　　要：粗糙集理论把知识看作是具有粒度的,引入了知识粗糙性的概念.本文主要讨论知识粗糙性与信息熵之间的关系,证明了熵与互信息对于由知识粗糙性定义的偏序"较细"都是单调下降的.通过反例说明,一般情况下,其逆关系是不成立的.同时给出了逆关系成立的条件.揭示了知识粗糙性实质上是其所含信息多少的更深层次上的刻划.Rough Set theory is a kind of new tool for dealing with imprecise knowledge. In this paper, relationships between roughness of knowledge and information entropy are mainly discussed. We prove that entropy and mutual information are decreasing for the partial order finer on knowledge. Through negative examples, we show that the inverse relationships between them are not valid. The conditions that satisfy the inverse relationships are also given. In fact, roughness of knowledge does deeply give a description of its information.

关 键 词：粗糙集理论 知识粗糙性 信息熵 人工智能 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]