基于粗集理论的属性约简关键技术概述  

Overview on Key Technologies of Attribute Reduction Based on Rough Set Theory

作　　者：郑涛[1] 杨丽君 Zheng Tao;Yang Lijun(Civil Aviation Flight University of China,Guanghan 618307 Sichuan China)

机构地区：[1]中国民用航空飞行学院,四川广汉618307

出　　处：《中国民航飞行学院学报》2021年第5期28-32,共5页Journal of Civil Aviation Flight University of China

基　　金：四川省科技厅面上项目(2020YJ0500)。

摘　　要：本文从静态属性约简和动态属性约简两个方面对基于粗集理论的属性约简关键技术进行了归纳总结,静态属性约简算法有基于信息熵、基于正域及基于辨识矩阵的约简算法,同智能计算方法结合的动态属性约简算法有并行属性约简、基于粒计算的属性约简及增量式属性约简等。指出今后属性约简的发展方向是在大数据时代下同智能算法、并行计算、云计算等技术融合发展的趋势。We summarize the key technologies of attribute reduction based on rough sets from two aspects:static attribute reduction algorithms based on information entropy,positive domain and identification matrix,and dynamic attribute reduction algorithms combined with intelligent computing methods including parallel attribute reduction,attribute reduction based on granular computing and incremental attribute reduction.It is pointed out that the future development direction of attribute reduction is the trend of integration with intelligent algorithms,parallel computing,cloud computing and other technologies in the era of big data.

关 键 词：粗集理论 属性约简 并行约简 增量式约简 粒计算 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]