TY - GEN
T1 - On the use of Machine Learning in Geotechnical Engineering
AU - Brinkgreve, Ronald
AU - Zekri, Ashraf
PY - 2024
Y1 - 2024
N2 - The use of Artificial Intelligence (AI) and Machine Learning (ML) have significantly increased over the last couple of years. ML is driven by the availability of data. Although geotechnical engineering is generally not among the first in picking up new technologies, there is a lot of data in our profession, and therefore, lots of opportunities to apply ML. In this article some examples are given of how ML can be used to facilitate and automate the geotechnical engineering workflow. Examples of soil identification, CPT interpretation, 3D soil stratification, parameter determination and surrogate modelling are given, and some other applications are mentioned.
AB - The use of Artificial Intelligence (AI) and Machine Learning (ML) have significantly increased over the last couple of years. ML is driven by the availability of data. Although geotechnical engineering is generally not among the first in picking up new technologies, there is a lot of data in our profession, and therefore, lots of opportunities to apply ML. In this article some examples are given of how ML can be used to facilitate and automate the geotechnical engineering workflow. Examples of soil identification, CPT interpretation, 3D soil stratification, parameter determination and surrogate modelling are given, and some other applications are mentioned.
M3 - Conference contribution
T3 - BAWKolloquium
SP - 15
EP - 23
BT - Bundesanstalt für Wasserbau Kolloquium Numerik in der Geotechnik
PB - Bundesanstalt für Wasserbau
T2 - BAW Kolloquium Numerik in der Geotechnik
Y2 - 7 November 2024 through 8 November 2024
ER -