北京航空航天大学学报 ›› 2006, Vol. 32 ›› Issue (01): 65-68.

• 论文 • 上一篇    下一篇

基于D-S证据理论的知识融合及其应用

韩立岩, 周芳   

  1. 北京航空航天大学 经济管理学院, 北京 100083
  • 收稿日期:2005-07-14 出版日期:2006-01-31 发布日期:2010-09-20
  • 作者简介:韩立岩(1955-),男,北京人, 教授, hanly1@163.com.

Knowledge fusion based on D-S evidence theory and its application

Han Liyan, Zhou Fang   

  1. School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2005-07-14 Online:2006-01-31 Published:2010-09-20

摘要: 知识融合是上世纪末提出的一种新概念,它不但能够融合数据、信息,而且还可对方法、经验,甚至人的思想进行融合.针对企业失败预警问题,提出了一种基于D-S(Dempster-Shafer)证据理论的新的知识融合方法,该方法主要包括数学建模、知识融合以及结果分析与决策三个步骤.给出了基于D-S证据理论知识融合方法的具体实现:提出了一种数学建模方法,将信息熵的概念引入到基础概率分配的确定中;针对企业失败预警问题,推导了基于D-S证据组合理论的知识融合公式;提出了一种简洁的融合结果分析与决策方法.最后通过对具有典型企业风险特性的两个上市公司进行分析和处理,验证提出的基于D-S证据理论的知识融合方法的有效性.结果表明,该方法能有效降低企业失败预警方法的不确定性.

Abstract: Knowledge fusion is a new concept proposed at the end of last century. The fused knowledge is referred as method, experience and idea as well as data and information. A new knowledge fusion method based on D-S(Dempster-Shafer) evidence theory was presented and applied to corporate failure prediction. There were three steps in the method: mathematic modeling, knowledge fusing and discriminating. The implementation of these steps was developed. The information entropy theory was employed to determine the basic probability assignment of knowledge. The knowledge fusing equation was induced following D-S evidence combination rule. A concise discriminating regulation was proposed to analyze the fusion result. The data of two listed companies was used to show the validity of the presented method. The results indicate this method can reduce the uncertainty of the prediction model effectively.

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