Artificial neural networks for predicting rockburst in deep mining

作者：Song Changsheng^*; Li Dehai

来源：International Symposium on Mining Science and Safety Technology, 2007-04-16 to 2007-04-19.

• deep mining
• rockburst
• nonlinear
• mining depth
• artificial neural network

Rockburst is a kind of dynamic instability phenomenon for surrounding rock mass in deep mining. It has complicated nonlinear relationship between rockburst and its factors. Based on the analysis of main factors influencing rockburst, the mining depth H, the ratio of rock's maximal tangential stress to rock's uniaxial compressive strength, the ratio of rock's uniaxial compressive strength to rock's uniaxial tensile strength, and the elastic energy index was selected as the prediction indexes of rockburst. The model to predict rockburst was established by applying the theory of artificial neural network (ANN). A large amount of on-site data was used as learning and training samples. Then the predicted results from the model and theoretical results are compared and analyzed. The results show that it is feasible and appropriate to select mining depth H as a main factor, the model is valid to predict rockburst in deep mining by ANN.

• 出版日期2007
• 单位河南理工大学