Innovative cone resistance and sleeve friction prediction from geophysics based on a coupled geo-statistical and machine learning process
Geotechnical parameters derived from an intrusive cone penetration test (CPT) are used to asses mechanical properties to inform the design phase of infrastructure projects. However, local, in situ 1D measurements can fail to capture 3D subsurface variations, which could mean less than optimal design...
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| Main Authors: | A. Bolève, R. Eddies, M. Staring, Y. Benboudiaf, H. Pournaki, M. Nepveaux |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2025-06-01
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| Series: | Artificial Intelligence in Geosciences |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666544125000061 |
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