Digital geotechnics: from data-driven site characterisation towards digital transformation and intelligence in geotechnical engineering-Reference-Cited by-同舟云学术

Digital geotechnics: from data-driven site characterisation towards digital transformation and intelligence in geotechnical engineering

Published:2023-11-06 Issue: Volume: Page:1-25
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:

Wang Yu¹^ORCID,Tian Hua-Ming¹

Affiliation:

1. Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, People’s Republic of China

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/10.1080/17499518.2023.2278136

Reference124 articles.

1. Alpaydin, E. 2020. Introduction to Machine Learning. Cambridge: MIT Press.

2. Numerical modelling of large deformation problems in geotechnical engineering: A state-of-the-art review

3. Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

4. Reliability and Human Factors in Geotechnical Engineering

5. Physics-informed deep learning for one-dimensional consolidation

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