Prediction of Rock Burst Intensity Based on Multi-Source Evidence Weight and Error-Eliminating Theory

Abstract

Abstract Rock burst is the main geological hazard in deep underground engineering. For the prediction of the intensity of rock burst, a model for prediction of rock burst intensity on the basis of multi-source evidence weight and error-eliminating theory was established. Four indexes including the ratio of rock′s compressive-tensile strength σc/σt , the stress coefficient of rock σθ/σc, the elastic energy index of rock Wet and integrality coefficient Kv were chosen as the prediction variables of rock burst, the index weights are calculated by different weighting methods, and fused with evidence theory to determine the final weight of each index. According to the theory of error-eliminating, taking no rock burst as the objective and using the error function to processed 18 sets of typical rock burst data at home and abroad, and the weight of evidence fusion as the normalized index limit loss value, and a model for prediction of rock burst intensity was build. It is verified by the actual situation and three other models. Finally, the model has been applied to rock burst prediction of Zhongnanshan tunnel ventilation shaft. The results show that evidence theory fuses multi-source index weights and improves the method of determining index weights. The index value is processed by Error-eliminating theory, and the limit value problem of index value normalization is optimized. The predicted results of the proposed model are consistent with the situation of Zhongnanshan tunnel. It improves the objectivity of the rock burst prediction process and provides a research idea for rock burst intensity prediction index.