OPTIMAL MODEL OF ROCKBURST PREDICTION BASED ON THE FUZZY NEURAL NETWORK

被引：0
|
作者：
Li, Kai-Qing [1 ]
He, Fu-Lian [2 ]
Xie, Sheng-Rong [1 ]
Zhang, Shou-Bao [1 ]
Han, Hong-Qiang [1 ]
He, Yong-Jun [1 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Civil & Environm Engn, Beijing 100083, Peoples R China
[2] China Univ Mining & Technol, Coll Resources & Safety Engn, Beijing 100083, Peoples R China
来源：
CONTROLLING SEISMIC HAZARD AND SUSTAINABLE DEVELOPMENT OF DEEP MINES: 7TH INTERNATIONAL SYMPOSIUM ON ROCKBURST AND SEISMICITY IN MINES (RASIM7), VOL 1 AND 2 | 2009年
关键词：
D O I：
暂无
中图分类号：
Q14 [生态学（生物生态学）];
学科分类号：
071012 ; 0713 ;
摘要：
The rockburst is one of the major disasters in coal mine. Because of the shortage of traditional methods to forecast rockburst, the method based on combining the fuzzy theory with artificial neural networks using MATLAB program is applied to predict rockburst with model optimization. The fuzzy neural network is also an information processing system combining the artificial neural network with the fuzzy theory, which can learn from incomplete and inaccurate data with strong noise, and has a very strong ability of error-tolerance. Meanwhile, by using the field rockburst monitoring data of Yaoqiao Coal Mine, the rockburst fuzzy neural network model is optimized. It is seen that the method is feasible and the result is satisfactory.
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页码：1161 / 1166
页数：6
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