JRMGE / Vol 14 / Issue 3
Editorial for Advances and applications of deep learning and soft computing in geotechnical underground engineering
Wengang Zhang, Kok-Kwang Phoon
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School of Civil Engineering, Chongqing University, China
Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, China
National University of Singapore, Singapore
Singapore University of Technology and Design, Singapore, Singapore
2022, 14(3): 671-673. doi:10.1016/j.jrmge.2022.01.001
Received: 2022-01-13 / Revised: / Accepted: 2022-01-19 / Available online: 2022-01-19
2022, 14(3): 671-673.
doi:10.1016/j.jrmge.2022.01.001
Received: 2022-01-13
Revised:
Accepted: 2022-01-19
Available online: 2022-01-19
We are privileged to be invited by the Honorary Editor-in-Chief, Professor Qihu Qian, Editor-in-Chief, Professor Xia-Ting Feng, and the editorial staff of the Journal of Rock Mechanics and Geotechnical Engineering (JRMGE), to serve as Guest Editors for this Special Issue (SI).
The purpose of this SI is to review the latest development of machine learning (ML) techniques including the soft computing (SC) and deep learning (DL) methods as well as their key applications in geotechnical underground engineering problems. The publication of this SI is timely given the significant interest and progress in data-centric geotechnics (Phoon and Ching, 2021). The International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE) TC309/TC304/TC222 3rd Machine Learning in Geotechnics Dialogue (3MLIGD) was convened on 3 December 2021 to foster greater connectivity between researchers and practitioners to accelerate progress in this nascent field of data-centric geotechnics. The SI contains 22 invited papers covering different ML models, their performance, and the challenges faced in real world applications.
Article Data
Author(s) Information
Prof. Wengang Zhang
zhangwg@cqu.edu.cn
Wengang Zhang is currently full professor in School of Civil Engineering, Chongqing University, China. He obtained his BSc and MSc degrees from the Hohai University in China and his PhD from Nanyang Technological University, Singapore. He is now the member of the International Society for society Mechanics and Geotechnical Engineering TC304 (Reliability), TC309 (Machine Learning), TC219 (System Performance of Geotechnical Structures) and TC222 (Building Information Modelling and Digital Twins). Dr. Zhang has been selected as the World's Top 2% Scientists in 2020 and 2021. He received 2021 Underground Space Outstanding Paper Award, Computers and Geotechnics Sloan Outstanding Paper Award, Tunnelling and Underground Construction Society (Singapore) Hulme Best Paper Award and the Best Referees 2020 of Geoscience Frontiers. He served as Associate Editor for Geoscience Frontiers, editorial board member of Journal of Rock Mechanics and Geotechnical Engineering and Georisk.
Prof. Kok-Kwang Phoon
kkphoon@nus.edu.sg
