Neighborhood-Based Set-Valued Double-Quantitative Rough Sets  

邻域集值双量化粗糙集

作　　者：LI Wen-tao LI Zhang ZHU Chun-long XU Wei-hua 李文涛;李璋;朱春龙;徐伟华(College of Artificial Intelligence,Southwest University,Chongqing 400715,China)

机构地区：[1]College of Artificial Intelligence,Southwest University,Chongqing 400715,China

出　　处：《Chinese Quarterly Journal of Mathematics》2021年第2期122-140,共19页数学季刊（英文版）

基　　金：Supported by the College Students Innovation and Entrepreneurship Training Program project(Grant No.101202010635586);National Natural Science Foundation of China(Grant No.61772002,61976245);Fundamental Research Funds for the Central Universities(Grant No.SWU119063);Scientific and Technological Project of Construction of Double City Economic Circle in Chengdu-Chongqing Area(Grant No.KJCX2020009);Science and Technology Research Program of Chongqing Education Commission(Grant No.KJQN202003806)。

摘　　要：Double-quantitative rough approximation,containing two types of quantitative information,indicated stronger generalization ability and more accurate data processing capacity than the single-quantitative rough approximation.In this paper,the neighborhood-based double-quantitative rough set models are firstly presented in a set-valued information system.Secondly,the attribute reduction method based on the lower approximation invariant is addressed,and the relevant algorithm for the approximation attribute reduction is provided in the set-valued information system.Finally,to illustrate the superiority and the effectiveness of the proposed reduction approach,experimental evaluation is performed using three datasets coming from the University of California-Irvine(UCI)repository.

关 键 词：Attribute reduction Double quantification Fuzzy similarity relation Setvalued information system 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]