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一种基于信息熵的模糊粗糙集知识获取方法
引用本文:阳琳谮,温明,卓晴,王文渊.一种基于信息熵的模糊粗糙集知识获取方法[J].计算机工程与应用,2008,44(23):59-61.
作者姓名:阳琳谮  温明  卓晴  王文渊
作者单位:清华大学,自动化系,北京,100084
摘    要:模糊粗糙集融合了模糊集和粗糙集的思想,是一种新的处理模糊和不确定性知识的软计算工具。针对属性为模糊值的信息系统,提出了一种基于熵的模糊粗糙集知识获取方法:首先通过模糊相似度量计算出各属性下对象的模糊相似值,再根据模糊相似关系构造模糊等价关系,然后根据模糊等价关系建立属性集的信息熵表示,继而使用基于信息熵的决策表属性约简算法获取规则。最后,通过一个实例,分析说明了这种算法的合理有效性。

关 键 词:模糊粗糙集  模糊相似度量  模糊等价关系  信息熵
收稿时间:2008-2-25
修稿时间:2008-5-13  

Entropy-based knowledge acquisition approach on fuzzy rough set
YANG Lin-yun,WEN Ming,ZHUO Qing,WANG Wen-yuan.Entropy-based knowledge acquisition approach on fuzzy rough set[J].Computer Engineering and Applications,2008,44(23):59-61.
Authors:YANG Lin-yun  WEN Ming  ZHUO Qing  WANG Wen-yuan
Affiliation:Department of Automation,Tsinghua University,Beijing 100084,China
Abstract:Fuzzy rough set,which combines the ideas of fuzzy set and rough set,is a new soft computing tool dealing with fuzzy and uncertain information.In this paper the authors propose an entropy-based knowledge acquisition approach to handle information system whose attribute values are fuzzy.Firstly,the authors calculate fuzzy indiscernibility values between objects in each attribute based on fuzzy similarity measure.With these values the authors can construct fuzzy equivalence relations among objects.Then the authors can calculate the information entropy of any attribute set.The entropy-based attribute reduction algorithm can be used to acquire rules.Finally,by an example,the approach is verified to be reasonable and effective.
Keywords:fuzzy rough set  fuzzy similarity measure  fuzzy equivalence relations  information entropy
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