A vague-rough set approach for uncertain knowledge acquisition
A vague-rough set approach for uncertain knowledge acquisition
复制标题
不确定知识获取的模糊粗糙集方法
DOI：
10.1016/j.knosys.2011.03.005
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发表时间：
2011-08-01
影响因子：
8.8
通讯作者：
Gou, Shirong
中科院分区：
文献类型：
--
作者：
Feng, Lin;Li, Tianrui;Gou, Shirong
将模糊数据处理中的模糊集和粗糙集结合起来，提出了一种不确定环境下知识提取的模糊-粗糙集方法。在Vague决策信息系统（VDIS）中，利用粗糙下近似分布、属性约简的概念和相容性矩阵计算所有属性约简。从VDIS中提取决策规则的研究结果表明，所提出的方法扩展了经典粗糙集理论中的相应方法，为不确定模糊知识的获取提供了一种新的途径。(C)2011 Elsevier B. V.保留所有权利。
By combining both vague sets and rough sets in fuzzy data processing, we propose a vague-rough set approach for extracting knowledge under uncertain environments. We compute all attribute reductions using the vague-rough lower approximation distribution, concepts of attribute reduction and the discernibility matrix in a vague decision information system (VDIS). Research results for extracting decision rules from the VDIS show the proposed approaches extend the corresponding method in classical rough set theory and provide a new avenue to uncertain vague knowledge acquisition. (C) 2011 Elsevier B.V. All rights reserved.