基于双极限对称相似关系的粗糙集模型

Yuming Zhai, Ruixia Yan
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引用次数: 1

摘要

提出了对称相似关系的可比性和可信度的概念。本文建立了双限制对称相似关系,并在此基础上构造了粗糙集模型。然后,确定上近似集、下近似集和边界域,以提高不完全信息系统中知识的粒度和准确性。从理论和实践两个方面验证了基于双极限对称相似关系的粗糙集模型的有效性和实用性。
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Rough set model based on dual-limited symmetric similarity relation
The concepts of comparability and credibility of the symmetric similarity relations are proposed. This paper builds a dual-limited symmetric similarity relation and construct the rough set model based on the dual-limited symmetric similarity relation. Then, this paper determine the upper approximation set, and lower approximate set and the boundaries domain to improve the granularity and accuracy of knowledge in incomplete information system. The effectiveness and practicality of the rough set model based on the dual-limited symmetric similarity relations are verified from the two aspects of theoretical and practice.
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