Study on Prediction Method of Building Settlement in Metro Protection Area
In order to accurately grasp the deformation trend of buildings and structures in the metro protection area and ensure the safety of buildings and structures,this paper gives full play to the advantages of empirical wavelet transform (EWT) and Elman neural network model in signal decomposition and data prediction,and constructs a new EWT-Elman combined prediction model. The main ways to realize the settlement prediction of buildings and structures in the metro protection area by the combined model are as follows:first,the EWT method is used to adaptively decompose the settlement deformation sequence of buildings and structures to obtain differ-ent components;secondly,Elman neural network model is used to predict different components;finally,the final prediction result is obtained by reconstructing the prediction values of different components. Two groups of measured settlement and deformation data of buildings in the metro protection area are used for experiments. The results show that the combined prediction model proposed in this paper has higher accuracy and adaptability than the individual Elman neural network model,which provides an effective reference for the settlement prediction of related types.
empirical wavelet transformmetro protection areaprediction of building settlementElman neural network model
万方数据
维普
