A deep learning-based surrogate model for probabilistic analysis of high-speed railway tunnel crown settlement in spatially variable soil considering construction process

Author:

Zhang Houle,Wu Yongxin,Cheng Jialiang,Luo Fang,Yang ShangchuanORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference48 articles.

1. A swarm intelligence-based machine learning approach for predicting soil shear strength for road construction: a case study at Trung Luong National Expressway Project (Vietnam);Bui;Eng. Comput-Germany.,2019

2. Surrogate modeling for interactive tunnel track design using the cut finite element method;Bui;Eng Comput-Germany,2023

3. Real-time risk assessment of tunneling-induced building damage considering polymorphic uncertainty;Cao;ASCE-ASME J Risk U A,2022

4. Quantification of prior knowledge in geotechnical site characterization;Cao;Eng. Geol.,2016

5. Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods;Chen;Soils Found.,2019

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