Gas content prediction based on BP neural network

The paper presented a BP neural network model to predict content of coalbed gas based on analyzing explored borehole data of No.13-1 coal bed of Panyi mine in Huainan coal mining area.It is determined that the coal burial depth,thickness,lithologic properties of roof and floor,and coal rank are the important factors controlling gas content of coal.And the model was trained and tested with experimental data.Predicting results of the model are more accurate and reliable than that of linear regression prediction model.