The amount prediction of gas emitted via wavelet neural network with improving training algorithm

Accurately predicting the amount of gas emitted from the mine is a very important matter for safety. As back-propagation neural networks (BPNN) have the shortcomings of slow convergence and easily falling into local optimums, wavelet neutral network (WNN) is applied to the prediction system with new amended training algorithm. The simulation results obtained show that the new prediction system has faster convergence and more accurate prediction.