Research on the Prediction of CO Concentration in Single-head Roadway Based on Curve Fitting and Neural Network
In order to realize the prediction of CO concentration in the single-head roadway of the mine,based on the monitoring data of CO concentration in the heading face of the single-head roadway in the 1800 transport lane of Laochang tin mine in Yunnan Province.Firstly,the MATLAB curve fitting toolbox was used to fit the curve of the change of CO concentration with time in the single-head roadway,and the mathematical model of the change of CO concentration with time in the single-head roadway of the mine was established.Through the model,the time required for the CO concentration value in the single-head roadway of the mine to reach the CO concentration value required by the safety regulations was obtained.Then,the convolutional neural network time series prediction model(CNN model)and the BP neural network time series prediction model(BP model)were used to predict the CO concentration,and the two evaluation indexes of R2 and RMSE were compared.The results show that the BP neural network time series prediction model has the better prediction effect on the CO concentration of the single-head roadway,which provides an accurate and reliable theoretical basis for the monitoring and control of the CO concentration value of the single-head roadway in the mine.
single-head roadwayMATLABcurve fittingconvolutional neural networkBP neural networktime series prediction
NETL
NSTL
万方数据
