Affiliations: Guangxi Key Laboratory of Cross-border E-commerce Intelligent Information Processing, Guangxi University of Finance and Economics, Nanning, Guangxi, P.R. China
Correspondence:
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Corresponding author. Sichun Wang, Guangxi Key Laboratory of Cross-border E-commerce Intelligent Information Processing, Guangxi University of Finance and Economics, Nanning, Guangxi 530003, P.R. China. E-mail: 1212@hnuc.edu.cn.
Note: [1] This work is supported by the Natural Science Foundation of Guangxi (2016GXNSFAA380282).
Abstract: An approximation space is one basic concept in rough set theory. This paper investigates measures of uncertainty for an approximation space from granular computing viewpoint. Granular structures of an approximation spaces are first described by means of set vectors. Then, relationships between granular structures of an approximation spaces are studied from the two aspects of dependence and separation. Next, properties of granular structures of an approximation space are given. Furthermore, as an application for granular structures of an approximation spaces, measuring uncertainty of approximation spaces is investigated. Finally, one example is employed to illustrate features of the proposed measures for uncertainty of approximation spaces. These results will be helpful for understanding the essence of uncertainty for an approximation space.
