摘要
粗糙集和软集等作为不确定性问题的研究方法,目前已成为智能计算的研究热点。本文首先构建了对象的可区分粒度矩阵,通过可区分粒度矩阵定义了一般多粒度软粗糙模糊上、下近似算子并研究一些主要的性质;其次,讨论了一般多粒度软粗糙模糊集的不确定性度量;最后,通过案例验证了该模型的应用效果。
As the research methods of uncertain problems,rough set and soft set have become theresearch hotspot of intelligent computing.Firstly,this paper constructs the discernible granularitymatrix of the object,defines the generalized multi-granulation soft rough fuzzy upper and lowerapproximation operators through the discernible granularity matrix,and studies some main properties.Secondly,the uncertain measures of generalized multi-granulation soft rough fuzzy set is discussed.Finally,the application effect of the model is verified by cases.
作者
刘玉锋
孙文鑫
LIU Yu-feng;SUN Wen-xin(City College of Science and Technology,Chongqing University,Chongqing 402160,China;Chongqing Water Resources and Electric Enginecring College,Chongqing 402160,China)
出处
《模糊系统与数学》
北大核心
2021年第5期164-174,共11页
Fuzzy Systems and Mathematics
基金
重庆市教委科学技术研究计划项目(KJQN202003806)
关键词
可区分粒度矩阵
模糊粗糙集﹔软集﹔多粒度
Discernible Granularity Matrix
Fuzzy Rough Set
Soft Set
Multi-granulation
