Rough集理论中知识与运算的矩阵表示  

GrM-based Representation of the Concepts and Operations in Rough Set Theory

作　　者：陈泽华[1,2] 谢刚[1] 谢珺[1] 谢克明[1] 

机构地区：[1]太原理工大学信息工程学院,太原030024 [2]Department of Computer Science,San Jose State University,CA,95112

出　　处：《计算机科学》2011年第2期222-224,228,共4页Computer Science

基　　金：国家自然科学基金项目(60975032);山西省青年自然科学基金项目(2010021016-1)资助。

摘　　要：同一问题在不同知识表示下算法难度不同。Rough集理论把知识定义为对对象的分类能力,并提供了一套基于代数系统的知识表达和处理方法。然而在代数表示下,知识的本质以及运算直观性较差,不易于理解。同济大学苗夺谦教授建立了知识与信息之间的关系,在此基础上给出了Rough集理论中概念和运算的信息表示,并给出了知识约简在代数和信息两种表示下的等价性证明。现进一步将知识及其运算表示成粒矩阵形式,继而给出了知识约简在代数、信息和粒矩阵3种表示下的等价性证明。Different representation for knowledge brings different difficulties in comprehension and programming.Knowledge is regarded as the classification ability according to available knowledge in Rough Set Theory,based on which,a set of algebraic definition for knowledge representation and operation was systematically proposed.However,it is relative difficult to help understand the essence of knowledge in view of algebraic description.Professor Miao in Tongji University built up relations between knowledge and information,he redefined Rough Set algebraic system by information concepts.Furthermore,he also provided equivalent proof for both definitions.In this paper,knowledge and its operation were expressed in form of granular matrix.The equivalent proofs for all three definitions mentioned above were given in this paper.

关 键 词：粒计算 ROUGH集理论 粒矩阵 粒关系矩阵 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]