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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Veröffentlicht in:	Automation in construction Jg. 165; S. 105516
Hauptverfasser:	Wu, Xianguo, Feng, Zongbao, Liu, Jun, Chen, Hongyu, Liu, Yang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2024
Schlagworte:	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-Zugang:	Volltext
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