Application of wavelet neural network in open-pit mine slope deformation prediction

improve the accuracy and reliability of the prediction of slope deformation displacement monitoring data, the predictive model of wavelet neural network based on BP algorithm is established. The GPS slope monitoring data in Shuichang iron mine are viewed as samples, and they are trained and predicted through making Matlab program. It indicates that the wavelet neural network predictive model had the more nimble effective approximation of function ability and the strong fault tolerance. With the example tested, the wavelet neural network predictive model have the high-precision and reliability in nonlinear time series prediction.