ANN Evaluation Method of Rock Burst Risk Under Different Mining Disturbance

For the problems that traditional assessment methods for rock burst have index unstable, the subjective weights of affecting factors and un-distinguished influence factors of mining and excavation, fuzzy mathematics is used to study risk assessment indexes and evaluation methods of rock burst under different disturbance of mining and excavation. By quantifying influence factors of rock burst, training the artificial neural network and calculating the results, the contribution weights of each influencing factor under different mining conditions were obtained, and mining and excavation ANN evaluation method of rock burst hazard was established. Through the analysis of typical case of rock burst, the weights of influencing factors on mining rock burst hazard evaluation were obtained, and we made a distinction between mining and excavation disturbance by using neural network model and correlation analysis. Based on rock burst risk assessment, the results showed that ANN evaluation results of rock burst risk under different mining disturbance conditions are more consistent with the engineering practice.