Application of fuzzy neural network in predicting the risk of rock burst
Rock burst is one of the coal and rock dynamical disasters that must be kept in mind in mining activities. With the increase of mining depth, the risk of rock burst becomes increasingly great. At present, the risk prediction for rock burst mostly is still in the stage of simple statistical study and single factor forecast, making the prediction precision be not a desired one. Using the knowledge of fuzzy mathematics and neural network, we propose a fuzzy neural network risk prediction model for rock burst trained with the improved BP algorithm based on the typical rock burst data. This method is an improvement of comprehensive index judgment and multi-index judgment with fuzzy mathematics. Practical engineering applications in Sanhejian Coal Mines indicate that this method is not only precise and simple, but also intelligent, with the predicted results well agreeing with the practical conditions. Therefore, this method can be applied to the relevant engineering projects with satisfactory results.
rock burst risk prediction fuzzy mathematics BP neural network
Sun Jian Wang Lian-guo Zhang Hua-lei Shen Yi-feng
State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining & T School of Sciences, China University of Mining & Technology, Xuzhou 221116, China
国际会议
The 6th International Conference on Mining Science & Technology ICMST 2009(第六届国际矿业科学技术大会)
徐州
英文
1-8
2009-10-18（万方平台首次上网日期，不代表论文的发表时间）