Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (5): 71-75.doi: 10.3969/j.issn.1000-565X.2010.05.014

• Computer Science & Technology • Previous Articles     Next Articles

Improvement of Fusion of Conflicting Evidence Based on Deviation

Zhang Qi  Liu Qun   

  1. Research Institute of Computer System,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2009-05-27 Revised:2009-09-16 Online:2010-05-25 Published:2010-05-25
  • Contact: 张齐（1963-），男，副教授，主要从事智能控制、信息处理、监控软件研究． E-mail:csqzhang@scut．edu．cn
  • About author:张齐（1963-），男，副教授，主要从事智能控制、信息处理、监控软件研究．
  • Supported by:

    广东省科技计划项目（2007B030100001）

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Abstract:

In the Dempster-Shafer evidence theory,the traditional D-S evidence combination rule fails to identify the actual conditions with highly conflicting evidence,which may result in contradicting conclusions.In order to solve this problem,this paper proposes an improved algorithm for the fusion of conflicting evidence,which detects and eliminates the conflicting evidence by calculating the deviation from all evidence to the average support level of the proposition,and amends the results to combine the evidence from different recognition frameworks.Numerical results show that the proposed method can effectively deal with the conflicts and achieve accurate identification,and that it is prior to other typical algorithms in terms of convergence and reliability.

Key words: Dempster-Shafer evidence theory, combination rule, conflicting evidence, fusion model, deviation