Prediction for segment strain and opening of underwater shield tunnel using deep learning method-Reference-Cited by-同舟云学术

Prediction for segment strain and opening of underwater shield tunnel using deep learning method

Published:2023-03 Issue: Volume:39 Page:100928
ISSN:2214-3912
Container-title:Transportation Geotechnics
language:en
Short-container-title:Transportation Geotechnics

Author:

Tan Xuyan,Chen Weizhong,Yang Jianping,Du Bowen,Zou Tao

Funder

Chinese Academy of Sciences

Joint Fund of the National Natural Science Foundation of China and the Karst Science Research Center of Guizhou Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Transportation,Civil and Structural Engineering

Reference34 articles.

1. Data-driven based machine learning models for predicting the deliverability of underground natural gas storage in salt caverns;Ali;Energy,2021

2. Dynamic prediction models of rock quality designation in tunneling projects;Arsalan;Transp Geotech,2021

3. Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate; 2014. arXiv:1409.0473.

4. Bao YQ, Li H. Machine learning paradigm for structural health monitoring. Struct Health Monit 2021; 20(4): 1353–1372. .

5. A comprehensive underground excavation design (CUED) methodology for geotechnical engineering design of deep underground mining and tunneling;Behrooz;Int J Rock Mech Min Sci,2021

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