覆盖粗糙集上下近似的分类  

Classification of lower and upper approximations on covering rough sets

作　　者：陈文[1] 郑若鹢[1] 刘绍清[1] 黄河清[1] 

机构地区：[1]福州职业技术学院计算机系,福州350108

出　　处：《信息技术》2012年第8期23-27,32,共6页Information Technology

基　　金：福建省教育厅资助项目(JB11320)

摘　　要：覆盖粗糙集是经典粗糙集理论的推广。对于其上下近似,从不同角度可以得到不同的定义。文中分析覆盖粗糙集不同上近似间的区别与联系,总结定义覆盖粗糙集上近似的方法。对样点进行详细地分类,提出强正点、弱正点,弱正边点、正边点以及对应的强负点、弱负点、弱负边点、负边点等概念。利用这些概念对覆盖粗糙集的上下近似进行分类,对各类上下近似的对偶性、正域负域及边界的可定义进行对比。通过上下近似的分类对比,可以定义出更多满足应用需要的上下近似。Covering rough set theory is an extension of the traditional rough set theory. Researchers proposed different definition sets of upper/lower approximations from different viewpoints. This paper proposes the concept of point-covering, under which those definition sets can be more clearly distinguished. Specifically, it proposes a number of concepts including strong-positive-point, weak- positive-point, weak-positive-border-point and corresponding strong-negative-point, weak-negative-point, and weak-negative-border-point. Those concepts are employed to classify different definition sets of upper/lower approximations. Duality and other properties of those definition sets are also discussed. Based on this work, more upper/lower approximation definition sets can be developed to suit the requirement of applications.

关 键 词：粗糙集 覆盖 分类 上近似 下近似 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]