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Double Quantitative Rough Set Model Based on Logical Disjunct Operation in Multi-Granulation Approximate Space
DOI: 10.12677/ORF.2017.74016, PDF, HTML, XML, 下载: 1,297  浏览: 2,338  科研立项经费支持

Abstract: Both the variable precision rough set and graded rough set are the generalized rough set models based on indiscernibility relation in single granulation approximate space. In the viewpoint of information quantitative, the variable precision rough set describes relative quantitative infor-mation, while graded rough set is used to represent the absolute quantitative information in ap-proximate space. The multi-granulation approximate space as a generalized approximate space is a natural expansion of classical approximation space. In order to study the rough set model that include characteristics of variable precision rough set and graded rough set. We combine them into a double-quantitative multi-granulation rough set model based on logical disjunct operation. Furthermore, the rough set regions and some basic mathematical properties of the proposed model are discussed in detail. This research provides a novel approach to knowledge discovery in multi-granulation approximate space based on rough set theory.

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