Deformation Prediction of a Deep Foundation Pit Based on the Combination Model of Wavelet Transform and Gray BP Neural Network

Author:

Liu Qiang1ORCID,Yang Chun-Yan1,Lin Li2

Affiliation:

1. College of Harbour and Coastal Engineering, Jimei University, Xiamen 361021, China

2. College of Civil Engineering, Fuzhou University, Fuzhou 350007, China

Abstract

The purpose of this study was to predict the deformation of a deep foundation pit based on a combination model of wavelet transform and gray BP neural network. Using a case of a deep foundation pit, a combination model of wavelet transform and gray BP neural network was used to predict the deformation of the deep foundation pit. The results show that compared with the traditional gray BP neural network model, the relative error of the combination model of wavelet transform and gray BP neural network was reduced by 2.38%. This verified that the combined model has high accuracy and reliability in the prediction of foundation pit deformation and also conforms to the actual situation of the project. The research results can provide a valuable reference for foundation pit deformation monitoring.

Funder

Natural Scientific Research Foundation of Fujian

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference24 articles.

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