摘要
粗糙集理论是一种新的处理不精确、不完全与不一致数据的数学工具.属性约简是粗糙集理论的重要研究内容之一,已有的属性约简算法主要是基于代数表示与信息表示的方法.同一问题在不同的知识表示下,其求解难度是不同的.文中从改变属性约简问题的知识表示入手,提出了该问题的一种新的表示方式——幂图;给出了基于幂图的属性约简搜索式算法,把属性约简计算问题转化为在幂图中的搜索问题.理论分析表明新算法是有效的,为属性约简研究提供了一条新的途径.
Rough set theory is a new mathematical tool to deal with imprecise, incomplete and inconsistent data. Attribute reduction is one of important issues in rough sets. Most existing algorithms are studied under both algebra and information representations. As problem solving under different knowledge representations corresponding to different difficulties, the new knowledge representation, called power graph, is presented in this paper. Searching algorithms based on power graph are also proposed, which can translate computing problem of attribute reduction into searching problem in power graph. The algorithms will provide a new method in attribute reduction and the efficiency of the method has been proved in theoretical analysis.
出处
《计算机学报》
EI
CSCD
北大核心
2009年第8期1486-1492,共7页
Chinese Journal of Computers
基金
国家自然科学基金(60475019
60775036)
博士学科点专项科研基金(20060247039)资助~~
关键词
粗糙集
属性约简
幂图
粒计算
知识表示
rough sets
attribute reduction
power graph
granular computing
knowledge repre- sentation
