Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (28): 151-153.DOI: 10.3778/j.issn.1002-8331.2009.28.045

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Novel knowledge reduction algorithm for fuzzy rough set

TAO Zhi,ZHANG Chun-xiao,SHANG Wei   

  1. College of Sciences,Civil Aviation University of China,Tianjin 300300,China
  • Received:2008-05-27 Revised:2008-09-05 Online:2009-10-01 Published:2009-10-01
  • Contact: TAO Zhi

新的模糊粗集知识约简算法

陶 志,张春晓,商 维   

  1. 中国民航大学 理学院,天津 300300
  • 通讯作者: 陶 志

Abstract: A kind of attribute relative reduction for fuzzy decision attribute dependent degree is proposed.With rough set theory and fuzzy decision attribute dependent degree applied in knowledge express system,the dependent degree of the knowledge supplied by condition attribute for the whole decision is described and relative importance degree and relative core is obtained.Based on relative core,attributes are selected one by one and inserted into relative core according to their importance degree until the whole condition attribute dependent degree is met.

Key words: fuzzy rough set, knowledge express system, fuzzy decision attribute dependent degree, relative reduction

摘要: 提出了一种基于模糊决策属性依赖度的属性相对约简算法。该算法利用粗糙集理论分析的方法,通过在知识表达系统中引入模糊决策属性依赖度的概念,来描述由条件属性所提供的知识对整体决策的依赖程度,并通过模糊决策属性依赖度定义了条件属性对模糊决策属性的相对重要性,以此作为启发式信息,可以方便地求出相对核,再以相对核作为求解最小相对约简的起点。按重要性的不同逐次选择重要属性添加到相对核中,直至其依赖度达到整体条件属性依赖度时为止。

关键词: 模糊粗糙集, 知识表达系统, 模糊决策属性依赖度, 相对约简

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