Application Research of Urban Settlement Prediction Based on Grey Neural Network Combination Model
In order to improve the prediction accuracy of urban subsidence,based on Grey Model(GM)and back propagation(BP)neural network prediction model,this paper constructs grey neural networks model(GNNM).Taking the average settlement of Shang-hai characteristic area obtained by SBAS-InSAR technology as the original sequence of the three prediction models,the prediction cal-culation is carried out,and the prediction results of the combined prediction model,grey model and BP neural network model are com-pared and analyzed.The experimental results show that compared with the single GM(1,1)and neural network prediction model,the GNNM(1,1)combined prediction model has higher prediction accuracy and stability,and the closer it is to the central urban area,the better the prediction effect.
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