The Research of Decision Information Fusion Algorithm Based on the Fuzzy Neural Networks

  • Authors:

  • Pei-Gang Sun;Hai Zhao;Xiao-Dan Zhang;Jiu-Qiang Xu;Zhen-Yu Yin;Xi-Yuan Zhang;Si-Yuan Zhu

  • Affiliations:

  • School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China and Shenyang Artillery Academy, Shenyang 110162, P.R. China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China;Shenyang Institute of Aeronautical Engineering, Shenyang 110034, P.R. China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, P.R. China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
  • Year:
  • 2007

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Abstract

A new decision information fusion algorithm based on the fuzzy neural networks, which introduces fuzzy comprehensive assessment into traditional decision information fusion technology under the "soft" decision architecture, is proposed. The process of fusion is composed of the comprehensive operation and the global decision through fusing the local decision of multiple sensors for obtaining the global decision of the concerned object at the fusion center. In the practical application, the algorithm has been successfully applied in the temperature fault detection and diagnosis system of hydroelectric simulation system of Jilin Fengman. In the analysis of factual data, the performance of the algorithm precedes that of the traditional diagnosis method.