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2009 Ninth International Conference on Hybrid Intelligent Systems
RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring
Shenyang, China
August 12-August 14
ISBN: 978-0-7695-3745-0
| ASCII Text | x | ||
| Yong Zhang, Qing-dong Du, Shi-dong Yu, Jeng-Shyang Pan, "RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring," Hybrid Intelligent Systems, International Conference on, vol. 1, pp. 467-470, 2009 Ninth International Conference on Hybrid Intelligent Systems, 2009. | |||
| BibTex | x | ||
| @article{ 10.1109/HIS.2009.96, author = {Yong Zhang and Qing-dong Du and Shi-dong Yu and Jeng-Shyang Pan}, title = {RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring}, journal ={Hybrid Intelligent Systems, International Conference on}, volume = {1}, year = {2009}, isbn = {978-0-7695-3745-0}, pages = {467-470}, doi = {http://doi.ieeecomputersociety.org/10.1109/HIS.2009.96}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Hybrid Intelligent Systems, International Conference on TI - RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring SN - 978-0-7695-3745-0 SP467 EP470 A1 - Yong Zhang, A1 - Qing-dong Du, A1 - Shi-dong Yu, A1 - Jeng-Shyang Pan, PY - 2009 KW - information fusion KW - RBF neural network KW - Kalman filtering KW - mine monitoring VL - 1 JA - Hybrid Intelligent Systems, International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HIS.2009.96
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.
Index Terms:
information fusion, RBF neural network, Kalman filtering, mine monitoring
Citation:
Yong Zhang, Qing-dong Du, Shi-dong Yu, Jeng-Shyang Pan, "RBF Neural Network Based on Fuzzy Evolution Kalman Filtering and Application in Mine Safety Monitoring," his, vol. 1, pp.467-470, 2009 Ninth International Conference on Hybrid Intelligent Systems, 2009
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