基于最小集合覆盖的属性约简算法  

An Attribute Reduction Algorithm of Rough Set based on the Minimal Covering Set

作　　者：刘敏[1] 段富[1] 刘超慧[1] 

机构地区：[1]太原理工大学计算机与软件学院,太原030024

出　　处：《电脑开发与应用》2008年第8期53-55,68,共4页Computer Development & Applications

基　　金：山西省回国留学人员科研基金资助项目(2007-27)

摘　　要：在粗糙集理论的各种应用中,属性约简算法具有重要的意义,因而对属性约简算法的研究一直是粗糙集理论研究中的重点问题之一。在对属性约简算法充分研究的基础上提出一种基于最小覆盖集的粗糙集属性约简算法,即通过构造知识系统的一种改进的相关矩阵将属性约简简化为最小覆盖问题。将该算法与文献[7]中的算法进行实验比较并对结果进行分析,实验结果表明,当随着数据量增大时该算法具有更小的时间复杂度。In the application of rough set theory, the algorithm for attribute reduction is important so it is always a focus of rough set theory. In this paper here, an attribute reduction algorithm of rough set based on the minimal covering set is proposed. The attribute reduction in rough set is simplified the problem of the minimal covering set by constructing the relation matrix of the knowledge system. At last, the experiment comparing this algorithm to the algorithm of the 7th reference. The result of experiment shows that the time complexity of this algorithm is lower than other algorithms.

关 键 词：粗糙集 属性约简 相关矩阵 最小覆盖集 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]