Prediction model for rockburst based on acoustic emission time series

Based on the features of acoustic emission(AE) time series monitored for rockburst, adopting the wavelet neural network and catastrophe theory, a new rockburst prediction model is established. Firstly, a wavelet neural network model based on the AE monitored is established to forecast the future AE. Secondly, a catastrophe prediction model for rockburst is founded based on AE forecasted. A practical example shows that the predicted AE time series has high prediction accuracy; and rockburst prediction are consistent with field situation. It is shown that the model has the advantages of high forecasting accuracy and strong practicality.