Predicting Water Irruption Quantity from Coal Floor Based on Wavelet Neural Network

Predicting water-irruption quantity from coal floor is of significance to coal mine safety production. It is complex nonlinear system related to influencing factors, Aimed at improving generalization, the predictive mode based on wavelet decomposition and artificial neural network was proposed, detailed learning algorithm was proposed and it was used in prediction. Both of the subsequent and the examination show that, the method generates more fast convergence rate, more precise forecast than traditional artificial neural network model, and it presents good abilities of learning and dissemination.