Dam deformation prediction based on EMD and GA-BP neural network
Liang Yue-j · Journal of Guilin University of Technology · 2015
A new algorithm based on EMD and genetic algorithm-BP neural network is proposed. First,to effectively separate the nonlinear trend of volatility of high frequency and low frequency components,the algorithm deformation sequence is decomposed by EMD. Then,genetic algorithm is used to optimize weights and threshold values of the BP neural network,to build a prediction model for each component. Finally,the predicted values of each component in the forecast is overlay. The calculation is analyzed and compared with grey GM( 1,1),regression analysis,common Carl filtering and GA-BP neural network. The results show that the method can build external and internal environment optimization platform. With generalization ability and an adaptive fitting,it ensures the optimal local prediction with higher precision forecasting,and can be applied to dam deformation prediction practically.