Attribute reduction for the double-quantitative rough set model based on logical difference of precision and grade
ZHANG Xian-yong
1. College of Mathematics and Software Science, Sichuan Normal University, Chengdu 610068, China; 2. Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
Abstract：Double quantification has a fundamental function to completely describe the approximate space in rough set theory, and the rough set model based on logical difference of precision and grade serves as a basic double-quantitative model. According to this model, this paper aims to deeply explore its attribute reduction in the two-category case. First, by virtue of the model approximations, basic properties of two-region preservation are discussed, and the reduct regarding two-region preservation is proposed and investigated. Then, by virtue of both the variable precision approximations and graded approximations, the reduct regarding four-region preservation is defined, and the hierarchical relationship between both reducts is obtained. Finally, both reducts and their hierarchy are illustrated by a statistical decision table. For double-quantitative attribute reduction, the reducts regarding two-region and four-region preservation exhibit generalization and fundamentality/guidance, respectively, thus providing some basic thoughts.
张贤勇. 精度与程度逻辑差双量化粗糙集模型的属性约简[J]. 系统工程理论与实践, 2015, 35(11): 2925-2931.
ZHANG Xian-yong. Attribute reduction for the double-quantitative rough set model based on logical difference of precision and grade. Systems Engineering - Theory & Practice, 2015, 35(11): 2925-2931.
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2015, Vol. 35 
