Abstract：For coal and gas outburst intensity forecast problems in coal mine, this paper used the immune genetic algorithm and least square support vector machine, selected maximum principal stress, gas pressure, gas content, lithology of roof, distance from the fracture of roof, coal seam thickness, mining vertical depth, absolute gas emission, relative gas emission, and nine main influence factors, analyzed the related factors of high degree with factor analysis method, and extracted public factors as input of IGA-LSSVM model, then established the prediction model of coal and gas outburst intensity based on factor analysis and IGA-LSSVM. The model was trained with 14 sets of data. Another 5 sets of data were selected as the test sample, and the model was used to forecast. Results show that after optimizing the parameters of LS-SVM with IGA, the model can effectively predict the coal and gas outburst intensity and error rate is 0.
王志宏，乔楠. 煤与瓦斯突出强度的IGA-LSSVM预测模型[J]. 辽宁工程技术大学学报(自然科学版), 2015, 34(7): 791-796.
WANG Zhihong, QIAO Nan. Prediction model of coal and gas outburst intensity based on IGA-LSSVM. Journal of LNTU.Natural Science, 2015, 34(7): 791-796.