Study on the Gas Content of Coal Seam Based on the BP Neural Network

AbstractThe prediction model for gas content in coal seam has been built based on the BP Neural Network to predict gas content accurately. And the model has been solved and forecasted by combining MATLAB programming with actual data. Moreover, the comparison analysis has been performed with the traditional prediction model based on multiple- regression. The results show that the non-linear gas content model related with basement buried depth and coal seam thickness etc could be established by utilizing the BP Neural Network. And its prediction accuracy and feasibility are better than the multiple-regression model. It is an ideal model for predicting gas content. It could provide some new ideas for the gas content prediction and the prevention and control for coal and gas outburst