Gas Outburst Prediction of Underground Working Face Based on ACA-FCM Algorithm

In view of problems of great limitation in actual application and bad precision of prediction result of current gas outburst prediction method, the paper proposed a gas outburst prediction method based on ACA-FAM algorithm. It analyzed basic principle and implementation steps of ACA-FAM algorithm. Taking data of gas outburst of underground working face of a Coal Mine in a certain period as example, it used ACA-FAM algorithm to make mining analysis for the data to find relations between gas outburst and influencing factors such as buried depth, coal seam thickness, gas content, daily advance, coal seam interval and daily output. The test result shows that prediction result of the method is uniform with actual monitoring record and the method has higher classified prediction performance.