4.7 Article

Fuzzy rough set theory for the interval-valued fuzzy information systems

期刊

INFORMATION SCIENCES
卷 178, 期 13, 页码 2794-2815

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2008.03.001

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fuzzy sets; rough sets; interval-valued fuzzy sets; interval-valued fuzzy information systems; knowledge reduction

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The concept of the rough set was originally proposed by Pawlak as a formal tool for modelling and processing incomplete information in information systems, then in 1990, Dubois and Prade first introduced the rough fuzzy sets and fuzzy rough sets as a fuzzy extension of the rough sets. The aim of this paper is to present a new extension of the rough set theory by means of integrating the classical Pawlak rough set theory with the interval-valued fuzzy set theory, i.e., the interval-valued fuzzy rough set model is presented based on the interval-valued fuzzy information systems which is defined in this paper by a binary interval-valued fuzzy relations R is an element of F-(i)(U x U) on the universe U. Several properties of the rough set model are given, and the relationships of this model and the others rough set models are also examined. Furthermore, we also discuss the knowledge reduction of the classical Pawlak information systems and the interval-valued fuzzy information systems respectively. Finally, the knowledge reduction theorems of the interval-valued fuzzy information systems are built. (c) 2008 Elsevier Inc. All rights reserved.

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