Prediction of Gas Emission in Mining Face Based on Deep Neural Network
In order to improve the safety of coal mine,a prediction method of gas emission based on deep neural network is designed,and the actual amount of gas emission in a coal mine is tested and analyzed.The results show that there are slight changes between the predicted results and the actual parameters,and the overall predicted results are consistent with the characteristics of the gas emission quantity,which can accurately feedback the emission quantity variation amplitude.The prediction error is located near 0,between-3 and 3,and presents a gradual decline along both sides.The prediction error of more than 75％parameters is within 1.75,and the prediction error is within the allowable range.This research is helpful to improve the effect of energy saving and emission reduction in coal mines,and has good practical significance.
gas emission quantitystoping facedeep neural networkprediction error
万方数据
维普
