Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan
This report presents the key talking points in the First Workshop on the Future of Machine
Learning in Geotechnics (FOMLIG), that include data infrastructure, geotechnical context …
Learning in Geotechnics (FOMLIG), that include data infrastructure, geotechnical context …
Implementation of Surrogate Models for the Analysis of Slope Problems
Numerical modeling is increasingly used to analyze practical rock engineering problems.
The geological strength index (GSI) is a critical input for many rock engineering problems …
The geological strength index (GSI) is a critical input for many rock engineering problems …
Back-Analysis of Structurally Controlled Failure in an Open-Pit Mine with Machine Learning Tools
A McQuillan, A Mitelman, D Elmo - Geotechnics, 2023 - mdpi.com
Over the past decades, numerical modelling has become a powerful tool for rock mechanics
applications. However, the accurate estimation of rock mass input parameters remains a …
applications. However, the accurate estimation of rock mass input parameters remains a …
[HTML][HTML] Prediction of rockfall hazard in open pit mines using a regression based machine learning model
IP Senanayake, P Hartmann, A Giacomini… - International Journal of …, 2024 - Elsevier
This study investigates the feasibility of implementing simple Machine Learning models to
make fast and reliable predictions of rockfall energies and run-outs at the base of highwalls …
make fast and reliable predictions of rockfall energies and run-outs at the base of highwalls …
Transfer learning based tunnel boring machine advance classification
PJ Unterlass, GH Erharter… - IOP Conference Series …, 2024 - iopscience.iop.org
Abstract Tunnel Boring Machines (TBMs) are well established in modern tunnel
construction, with monitoring and predicting TBM performance being crucial for project …
construction, with monitoring and predicting TBM performance being crucial for project …
Examining the reliability of integrating machine learning with rock mass characterization and classification data
B Yang - 2024 - open.library.ubc.ca
The past decade has seen a significant increase in the use of machine learning (ML) in rock
engineering. While ML has the potential to revolutionize rock engineering by increasing …
engineering. While ML has the potential to revolutionize rock engineering by increasing …