Micro-seismic Hypocenter Disaster Prediction Based on Support Vector Machine

The micro-seismic monitoring system is adopted to monitor the real time and on-line state of underground mine. Due to the hypocenter affected by the external factors and internal mechanical properties, these parameters most reflecting hypocenter features are selected to be analyzed, which can make the treatment process more simple and accurate. By using the experience learning ability and the principle of minimized structural risk of the support vector machine, the collec-t ed data is normalized to establish the prediction model based on support vector machine. The test results indicate that it can meet the requirements of rapid and accurate data processing for micro-seismic hypocenter real-time and on-line monito-r ing system, achieving the practical purpose of mine safety monitoring.