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RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring

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4 Author(s)
Yong Zhang ; Software Coll., Shenyang Normal Univ., Shenyang, China ; Qing-Dong Du ; Shi-dong Yu ; Jeng-Shyang Pan

Fuzzy information fusion methods are adopted widely to resolve the complicated nonlinear problems in recent years. This paper proposes a fusion learning algorithm of radial basis function (RBF) neural network based on fuzzy evolution Kalman filtering. By using this proposed method, monitoring data are extracted and optimized in mine safety monitoring, and Matlab simulation results are analyzed. The results show that this method has feasibility and rapid learning efficiency, which can improve precision and reliability in mine monitoring systems.

Published in:

Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on  (Volume:1 )

Date of Conference:

12-14 Aug. 2009