DIAPHRAGM WALL'S DEFORMATION FORECASTING BASED ON BP-RBF NEURAL NETWORKS
Ning Li · Engineering Mechanics · 2009
A artificial neural network is adopted to forecast diaphragm wall's deformations.Five parameters,the soil's cohesion C,the soil's internal friction angle ,the wall's height H,the excavation depth H1 and the survey point's depth h,governing diaphragm wall's deformation are abstracted and taken as inputs of the artificial neural network model.A new hybrid neural network model,BP-RBF Neural Network Model is established by combining the traditional BP and RBF neural network.This new neural network model shows great superiority in higher efficiency and a simpler network structure compared with the traditional pure BP neural network model,at the same time the forecasting accuracy is ensured.