4.4 Article

On generalization of rough sets by using two different methods

期刊

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
卷 35, 期 1, 页码 979-993

出版社

IOS PRESS
DOI: 10.3233/JIFS-172078

关键词

delta beta(j)-opensets; boolean AND(beta j)-sets; rough sets; lower and upper approximations; accuracy measure

向作者/读者索取更多资源

Rough set theory was introduced by Pawlak in 1982 to handle imprecision, vagueness, and uncertainty in data analysis. It is dealing with vagueness (ambiguous) of the set by using the concept of the lower and upper approximations of objects based on an equivalence relation. The main idea of rough sets corresponds to study these approximations. So, in this paper, we generalize these approximations in the frameworks of topological spaces. The lower and upper approximations of Pawlak's model are replaced by interior and closure notions of the topological space. The set approximations are defined using the new topological notions delta(beta j)-open sets and boolean AND(beta j)-sets. Such techniques open the way for more topological applications in rough context and help in formalizing many applications from real-life data. The current extension approximations are satisfied all properties of original rough set theory without any conditions or restrictions. Comparisons between the current approximations and the previous one are introduced and shown to be more general.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据