基于相似关系的集值决策信息系统的属性约简  

Attribute reduction based on similar relation in set-valued decision information system

作　　者：王映龙[1,2] 华佳佳 杨珺 钱文彬[1,2] 

机构地区：[1]江西农业大学计算机与信息工程学院,南昌330045 [2]江西省高等学校农业信息技术重点实验室,南昌330045

出　　处：《计算机工程与应用》2018年第5期122-126,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61502213;No.61462038);江西省自然科学基金(No.20151BAB217009;No.20132BAB201045);江西省教育厅科学技术项目(No.GJJ150399)

摘　　要：属性约简是粗糙集理论中重要研究内容,由于现实应用领域中决策信息系统往往呈现出不完备性特点,为此,首先将不完备决策表转化为集值决策信息系统,并详细分析了集值决策信息系统下基于相似关系的分布约简和最大分布约简,在此基础上,构造了一种基于可区分对象集的属性约简算法,算法利用可区分对象集的集对,计算极小析取范式求解出所有的分布约简和最大分布约简。最后,利用实例分析验证了算法的有效性。Attribute reduction is an important issue in rough set theory, since the decision information systems are often included incomplete data in practical applications. Therefore, the incomplete decision table is transferred into a set-valued decision information system, and then the distribution reduction and the maximum distribution reduction based on similar relation in the set-valued decision information system are analyzed. On this basis, an attribute reduction algorithm based on the distinguishable set of objects is proposed, which uses the distinguishable set of objects' sets. All results of the distribution reduction and the maximum distribution reduction are calculated by the minimum disjunctive normal form.Finally, an illustrative example shows the feasibility of the algorithm.

关 键 词：粗糙集 不完备决策表 集值决策信息系统 可区分对象集 分布约简 最大分布约简 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]