基于粗糙集数据分析的可拓推理机制研究  

Research on Extension Reasoning Methods Based on Rough Set Data Analysis

作　　者：赵锐[1] 余永权[1] 张静[1] 

机构地区：[1]广东工业大学计算机学院,广州510006

出　　处：《计算机科学》2010年第12期167-170,共4页Computer Science

基　　金：国家自然科学基金项目可拓检测的物元机制研究(60272089)资助

摘　　要：目前可拓变换推理中的可拓变换主要依靠历史资料、人为指定或过往经验来进行,这大大制约了可拓变换在智能化推理中的应用。为解决此问题,提出了一种基于粗糙集数据分析的可拓推理机制。该机制首先采用粗糙集对数据进行分析来获取分类及规则知识,然后利用这些知识来指导可拓推理,从而实现了可拓变换及推理的可控性和高效性,为可拓推理的智能化应用奠定了基础。In the old extension transformation reasoning,extension transformation used historical information or personalexperience,which restricted its application in intelligentized reaso-ning.For solving the problem,an extension reasoning method based on rough set data analysis was proposed.The method gained some classified and rule knowledge by analyzing data with rough set firstly,then used the information to guide extension reasoning,which will make extension transformation reasoning become easy control and good efficiency and lay a foundation for its application in intelligentized reasoning.

关 键 词：可拓推理 粗糙集 数据分析 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]