Analysis and prediction of dam deformation based on wavelet de-noise and BP neural network
Fei Gao · Yangtze River · 2011
Based on deformation monitoring data of Gangkouwan dam,using Matlab,wavelet denoise,BP neural network,we establish deformation monitoring BP neural network models on the basis of time sequence and environment factors respectively.And the two models are both applied to predict deformation of a monitoring point of the dam.The time sequence BP neural network model has simple structure and quick learning speed,however,the BP neural network model based on environmental factors can effectively reflect the deformation factors,which is more efficient for fit and prediction of complex deformation and can better reveal the deformation law of a dam.Before applying BP network to forecasting,the original data is de-noised through wavelet analysis method and the advanced BP algorithm such as additional momentum method is adopted in the training process,which significantly improve the accuracy and speediness of BP network predictor and avoid it falling local minimum.Therefore,satisfying fitting effects and forecasting precision are obtained.