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一种非对称距离下的粗糙粒结构选择方法OACHSSCDCSTPCD

A Method for Selecting Rough Granular Structure Based on Asymmetric Distance

中文摘要英文摘要

针对目标信息系统中粒结构在近似求解中的选择问题,给出一种非对称距离下的粗糙粒结构选择方法.首先,在商空间知识距离框架下定义了一种非对称知识距离,用以刻画条件知识与目标概念之间的近似程度.其次,在同一目标信息系统中,按条件属性的不同添加顺序,建立相应的非对称知识距离序列.再次,在属性代价约束条件下,引入粗糙粒结构评价参数.最后,选择评价参数较小的粗糙粒结构逐级进行求解.

Aiming at the selection of granular structures for approximate solutions in target information systems,a method for selecting rough granular structures based on asymmetric distance is proposed.Firstly,an asymmetric knowledge distance is defined to describe the closeness between conditional knowledge and the target concept within the knowledge distance framework of quotient space.Subsequently,asymmetric knowledge distance sequences are constructed according to different orders of adding conditional attributes in the same target information system.Furthermore,an evaluation parameter for rough granular structure is introduced under the constraint of attribute cost.Finally,the rough granular structure with smaller evaluation parameters is selected for step-by-step approximation.

陈志恩

宁夏师范大学 数学与计算机科学学院,宁夏 固原 756000

数学

非对称距离粗糙粒结构属性代价约束条件评价参数

asymmetric distancerough granular structureattribute costconstraint conditionevaluation parameter

《宁夏大学学报(自然科学版)》 2024 (002)

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国家自然科学基金资助项目(12261070);宁夏自然科学基金资助项目(2024A0714);宁夏高等学校科学研究基金资助项目(NGY2022083)

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