Soft Rough Approximation Operators and Related Results | Zendy

Zhaowen Li | Zendy; Bin Qin | Zendy; Zhangyong Cai | Zendy

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Soft Rough Approximation Operators and Related Results

Author(s) -

Zhaowen Li,

Bin Qin,

Zhangyong Cai

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/241485

Subject(s) - rough set , soft set , mathematics , dominance based rough set approach , space (punctuation) , set (abstract data type) , computer science , data mining , artificial intelligence , programming language , fuzzy logic , operating system

Soft set theory is a newly emerging tool to deal with uncertain problems. Based on soft sets, soft rough approximation operators are introduced, and soft rough sets are defined by using soft rough approximation operators. Soft rough sets, which could provide a better approximation than rough sets do, can be seen as a generalized rough set model. This paper is devoted to investigating soft rough approximation operations and relationships among soft sets, soft rough sets, and topologies. We consider four pairs of soft rough approximation operators and give their properties. Four sorts of soft rough sets are investigated, and their related properties are given. We show that Pawlak's rough set model can be viewed as a special case of soft rough sets, obtain the structure of soft rough sets, give the structure of topologies induced by a soft set, and reveal that every topological space on the initial universe is a soft approximating space

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