一种基于区分矩阵的属性组合权重构造方法  

Approach of Ascertaining Combinatorial Attribute Weight Based on Discernibility Matrix

作　　者：叶军[1] 王磊[1] 

机构地区：[1]南昌工程学院信息工程学院,南昌330099

出　　处：《计算机科学》2014年第11期273-277,共5页Computer Science

基　　金：国家自然基金地区科学基金项目(61363047);国家自然基金(61461032);江西省自然基金(2011ZBAB201005);南昌工程学院青年基金项目(2010KJ019)资助

摘　　要：详细分析了以基于Pawlak的属性重要度来构造属性权重的方法存在的问题,给出了一种基于区分矩阵的属性重要度的定义方法,并且得到了该定义方法的一些重要性质。在此基础上提出了一种新的信息系统属性权重构造方法,新方法是以条件属性在整个信息系统中的贡献度来确定属性权重,不仅反映了属性自身区分对象的能力,而且体现了各属性在整个条件属性中的分类能力。通过算例分析表明,该方法得到的属性权重更加贴近事实,因此它能提高属性权重的准确度。The problems existed in the Pawlak attribute importance based method by which the attribute weight is constructed were analyzed in detail firstly,then a discernibility matrix based definition of attribute importance was given.On this basis,a novel approach for constructing the combinatorial attribute weights of information systems was proposed.In this approach,the attribute weights are ascertained according to the condition attribute’s contribution in the whole information system.The proposed approach not only reflects the ability of condition attributes to distinguish the object,but also reflects the classification capability of each attribute in the whole condition attributes.The numerical example demonstrates that the attribute weights gained by the proposed approach are more closer to the facts,so the proposed approach can improve the accuracy of the attribute weights.

关 键 词：粗糙集 区分矩阵 属性重要度 权重 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]