Grading Prediction of rockburst intensity based on entropy and normal cloud model

Rockburst is one of the main engineering geological hazards occurring in the deep underground engineering construction. The classification of rockburst is an important issue which must be resolved in many underground engineering. Four quantitative indices including the ratio of rock's compressive-tensile strength sigma(c)/sigma(t), the stress coefficient of rock sigma(theta)/sigma(c), the elastic energy index of rock Wet and integrality coefficient K-v are chosen as the predictor variables of rockburst, according to the unascertained factors of classification prediction of rockburst. The entropy method is adopted to determine the weighting coefficient for each evaluation index. Based on entropy method and the unascertained measurement theory, with 12 groups of typical engineering examples, rockbursts at home and abroad, an entropy and the normal cloud model to predict the possibility and classification of rockburst is established. Then the proposed model is validated with twelve typical rock projects and compared with the results of the technique for order preference by similarity to ideal solution method, the radial basis function-auto-regression method and the actual records. And then the model has applied to rockburst predicting calculation of Zhongnanshan tunnel ventilation shaft to study the effectiveness and feasibility of the model. The obtained results show a good agreement with practical rockburst classification. The results show the normal cloud model effective and available, and can be applied to the prediction for the possibility and classification of rockburst intensity in deep underground engineering.