OPTIMAL MODEL OF ROCKBURST PREDICTION BASED ON THE FUZZY NEURAL NETWORK
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.
KAI-QING LI FU-LIAN HE SHENG-RONG XIE SHOU-BAO ZHANG HONG-QIANG HAN YONG-JUN HE
School of Civil and Environmental Engineering, University of Science and Technology Beijing Beijing College of Resources & Safety Engineering, China University of Mining & Technology (Beijing) Beijing
国际会议
The 7th International Symposium on Rockburst and Seismicity in Mines(2009年第七届国际岩爆与微振动性学术研讨会)
大连
英文
1161-1166
2009-08-21（万方平台首次上网日期，不代表论文的发表时间）