多粒度粗糙集模型  

On a Multi-Granularity Rough Set

作　　者：黄卫华[1,2] 

机构地区：[1]文山学院数学学院,云南文山663099 [2]山西大学计算智能与中文信息处理教育部重点实验室,太原030006

出　　处：《西南师范大学学报（自然科学版）》2017年第5期137-143,共7页Journal of Southwest China Normal University(Natural Science Edition)

基　　金：国家自然科学基金项目(11361074);云南省教育厅科研基金项目(2015Y470);文山学院重点学科数学建设基金项目(12WSXK01)

摘　　要：把Pawlak粗糙集模型从经典的单粒度粗糙集模型扩展到多粒度粗糙集模型,用论域上的多个等价关系定义了集合的近似.研究了多粒度粗糙集模型的一些数学性质,定理表明Pawlak粗糙集的许多性质是多粒度粗糙集的特殊情况,并且使用多粒度定义的近似度量优于单粒度定义的度量,该度量更适合描述概念的精度并利于解决用户需求的问题.The Pawlak rough set model is mainly focused on the approximation of sets described by single binary relation on the universe. In the view of granular computing,classical rough set model has been re-searched by single granulation. The Pawlak rough set model has been extended in this paper to multi-gran-ulation rough set model, where the set approximations are defined by multi-equivalences on the universe. Mathematical properties of multi- granulation rough set have been investigated. Theorems show that some properties of Pawlak rough set are special circumstances of the multi-granulation rough set, approximation measure of set described by using multi-granulation is superior to by using single granulation, which is for describing more accurately the concept and solving problem according to user requirement.

关 键 词：粗糙集 多粒度 近似度量 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]