A Research on the Improved Information Fusion Algorithm

Author:

Zhang Guo Dong1,Qi Rui Min1

Affiliation:

1. Zheng Zhou Hua Xin College

Abstract

In the field of information confusion, evidence theory takes advantage of its uncertainties. But in practical evidences are always mutually independent, However, multi-source information fusion is a comprehensive integration and then obtaining decision-making, sometimes the result of information fusion give us wrong conclusion. So an improved information fusion algorithm is proposed in this paper. It can heighten the information confusion reliability and accuracy in a practical example.

Publisher

Trans Tech Publications, Ltd.

Reference6 articles.

1. H. L. Li, Y. M. Shi: Bays information fusion Based on the D-S evidence theory, Fuzzy systems and Science, Vol. 7 (2009), pp.46-51.

2. X. B. Xu, C. L. Wen and C. Ying: The fault diagnosis method of random sets Based on the fuzzy fault feature information measurement information fusion. Journal of Electronics & Information Technology, Vol. 7 (2009), pp.1635-1640.

3. B. Otman, X. H. Yuan: Engine fault diagnosis based on multi-Sells or information fusion using Dempater Sharer evidence theory, Information Fusion, Vol. 25 (2005) No. 1, pp.1-8.

4. Robert F B: Reformulating Decision Theory Using Fuzzy Set Theory and Shafer's Theory of Evidence, Fuzzy sets and systems, Vol. 136 (2003) No. 10, pp.243-266.

5. W. L. Li, K. H. Guo: D-S theory of evidence combination rule about conflict, Systems engineering theory and Practice, (2010) No. 8, pp.1422-1432.

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