The invention discloses a membrane bag sand
levee slope settlement prediction method and
system based on a neural network, and belongs to the technical field of prediction systems.The method comprises the steps that construction parameters, foundation
monitoring data and
geological exploration data of a membrane bag sand
levee slope are obtained; performing
feature fusion by analyzing correlation between the construction parameters and the compression amount of each foundation soil layer in the time dimension and between the foundation
monitoring data and the compression amount of each foundation soil layer to obtain fusion
time sequence features; and on the basis of the
geological exploration data, using a settlement prediction model and fusion
time sequence characteristics, predicting each compression amount by analyzing the pore
drainage rate of each foundation soil layer, outputting a settlement prediction result of the membrane bag sand
bank slope, identifying the settlement abnormal risk of the membrane bag sand
bank slope, and outputting the
settlement risk grade of a preset construction point. Therefore, by implementing the method and the device, the problem that the predicted total settlement amount of the film bag sand
bank slope is not accurate enough due to the fact that the influence of the bank slope foundation structure on the settlement amount in the construction process is not completely considered in the prior art can be solved.