Predicting existing tunnel deformation from adjacent foundation pit construction using hybrid machine learning

To accurately predict the existing tunnel deformation from adjacent foundation pit construction (AFPC), a hybrid prediction framework based on random forest recursive feature elimination and the Bayesian optimization natural gradient boosting algorithm (RF-RFE-BO-NGBoost) is presented in this paper....

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Bibliographic Details
Published in:Automation in construction Vol. 165; p. 105516
Main Authors: Wu, Xianguo, Feng, Zongbao, Liu, Jun, Chen, Hongyu, Liu, Yang
Format: Journal Article
Language:English
Published: Elsevier B.V 01.09.2024
Subjects:
Adjacent foundation pit construction
Existing tunnel
Feature selection
Natural gradient boosting algorithm
Random forest recursive feature elimination
Shapley additive ExPlanations
Existing tunnel
Random forest recursive feature elimination
Feature selection
Natural gradient boosting algorithm
Adjacent foundation pit construction
Shapley additive ExPlanations
ISSN:0926-5805
Online Access:Get full text
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Summary:To accurately predict the existing tunnel deformation from adjacent foundation pit construction (AFPC), a hybrid prediction framework based on random forest recursive feature elimination and the Bayesian optimization natural gradient boosting algorithm (RF-RFE-BO-NGBoost) is presented in this paper. The key findings from this study include the following: (1) RF-RFE effectively screens out crucial parameters, with the optimal feature subset postscreening encompassing ten influencing factors. (2) The BO-NGBoost-based prediction model for existing tunnel deformation from AFPC achieves high accuracy, with R2 values ranging from 0.914 to 0.935, RMSE values ranging from 0.104 to 0.364, MAE values ranging from 0.089 to 0.335, and MAPE values ranging from 3.08% to 10.71% (3) SHapley Additive ExPlanations (SHAP) determines the contribution of each parameter, identifying important construction parameters influencing existing tunnel deformation. The hybrid prediction framework proposed herein provides guidance for realizing the excavation safety management of existing tunnels. •A method for predicting the adjacent existing tunnel deformation caused by foundation pit construction is proposed.•RF-RFE is used to screen out important parameters and BO-NGBoost is used to predict existing tunnel deformation.•The contribution of each parameter to the model output is analyzed using SHAP.•A tunnel construction example in China is taken as an example for verification.
ISSN:0926-5805
DOI:10.1016/j.autcon.2024.105516