Research on Predictive Model of Gas Concentration for Driving Ventilation in Coal Mine Based on Neural Network

In order to predict accurately gas concentration in driving ventilation process under different gas emission and different ventilation scheme conditions in coal mine, based on the analysis of various ventilation factors, the prediction model structure of gas concentration of driving ventilation was designed based on RBF neural network in this paper. Then MATLAB software and the observation data obtained from the coal mine sites were used to establish and test the prediction models of gas concentration in driving ventilation process based RBF. And then the better accuracy and performance prediction model based on RBF were obtained through testing and comparative analysis. Finally, the prediction model of gas concentration was applied to forecast gas concentration of heading face under different driving ventilation equipment layout and configuration parameters in the actual coal mine and then confirm the reasonable effective and energy-saving driving ventilation equipment layout and configuration parameter scheme. The research results can provide a certain theory basis for dynamics prediction of gas concentration and ventilation scheme optimization in the driving ventilation process.