Special issue on “Machine learning and AI in geotechnics”-Reference-Cited by-同舟云学术

Special issue on “Machine learning and AI in geotechnics”

Published:2023-01-02 Issue:1 Volume:17 Page:1-6
ISSN:1749-9518
Container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
language:en
Short-container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

Author:

Phoon K. K.¹,Zhang L. M.²,Cao Z. J.³

Affiliation:

1. Singapore University of Technology and Design

2. Hong Kong University of Science and Technology

3. Southwest Jiaotong University

Publisher

Informa UK Limited

Subject

Geology,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17499518.2023.2185938

Reference26 articles.

1. Burland, J. B. 1987. “The Teaching of Soil Mechanics – A Personal View.” Proceedings, 9th European Conference on Soil Mechanics and Foundation Engineering, Dublin, Vol. 3, 1427–1447.

2. Multi-fidelity data-driven modelling of rate-dependent behaviour of soft clays

3. Cross-project utilisation of tunnel boring machine (TBM) construction data: a case study using big data from Yin-Song diversion project in China

4. A real-time intelligent classification model using machine learning for tunnel surrounding rock and its application

5. A novel long-short term memory network approach for stress model updating for excavations in high stress environments

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