Prediction of gas emission from pre-pumped coal seam drilled along bedding based on Stacking integrated model

Due to the complex geology of coal seam, the prediction accuracy of gas emission is limited. The prediction of pre-pumped coal seam gas emission based on the Stacking integrated model is put forward. The normalization processing technology is used to pretreat the coal seam data from the pre-pumped coal seam drilling along the strata. Statistical analysis and machine learning algorithm are used to filter the eigenvalues of the processed data. A prediction model based on the Stacking integrated model is constructed to predict the gas emission in pre-pumped coal seam from drilling along the bedding. The experimental results show that compared with the traditional forecasting method, this method shows higher prediction accuracy and wider applicability.