Rough set theory for the interval-valued fuzzy information systems
Rough set theory for the interval-valued fuzzy information systems
复制标题
区间值模糊信息系统的粗糙集理论
DOI：
10.1016/j.ins.2007.12.005
复制
发表时间：
2008-04-15
影响因子：
8.1
通讯作者：
Chen, Degang
中科院分区：
文献类型：
--
作者：
Gong, Zengtai;Sun, Bingzhen;Chen, Degang
粗糙集的概念最初是由Pawlak[Z.Pawlak，Rough Sets，International Journal of Computer and Information Science，11(5)(1982)341-356]提出的。后来，Dubois和Prade[D.Dubois，H.Prade，Rough FuzzySets and FuzzyRough Sets，International Journal of General System 17(2-3)(1990)191-209]引入了粗糙模糊集和模糊粗糙集作为粗糙集的推广。将经典的Pawlak粗糙集理论与区间值模糊集理论相结合，研究了区间值模糊信息系统，讨论了区间值模糊信息系统的基本粗糙集理论。本文首先分别在经典Pawlak逼近空间和广义逼近空间中定义了区间值模糊集在论域U上的粗逼近，即建立区间值粗模糊集模型的空间。其次，研究了逼近算子的几个有趣性质，并研究了区间值粗糙模糊集模型在经典Pawlak逼近空间和广义逼近空间中的相互关系。第三，讨论了区间值模糊信息系统的属性约简。最后，结合实例给出了区间值模糊信息系统的知识发现方法。(C)2007 Elsevier Inc.保留所有权利。
The notion of a rough set was originally proposed by Pawlak [Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences 11 (5) (1982) 341-356]. Later on, Dubois and Prade [D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, International Journal of General System 17 (2-3) (1990) 191-209] introduced rough fuzzy sets and fuzzy rough sets as a generalization of rough sets. This paper deals with an interval-valued fuzzy information system by means of integrating the classical Pawlak rough set theory with the interval-valued fuzzy set theory and discusses the basic rough set theory for the interval-valued fuzzy information systems. In this paper we firstly define the rough approximation of an interval-valued fuzzy set on the universe U in the classical Pawlak approximation space and the generalized approximation space respectively, i.e., the space on which the interval-valued rough fuzzy set model is built. Secondly several interesting properties of the approximation operators are examined, and the interrelationships of the interval-valued rough fuzzy set models in the classical Pawlak approximation space and the generalized approximation space are investigated. Thirdly we discuss the attribute reduction of the interval-valued fuzzy information systems. Finally, the methods of the knowledge discovery for the interval-valued fuzzy information systems are presented with an example. (C) 2007 Elsevier Inc. All rights reserved.