A generic framework for geotechnical subsurface modeling with machine learning
This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning (ML) methods. Instead of using XY coordinate fields directly as model input, a series of autocorrelated geotechnical distance fields (GDFs) i...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2022-10-01
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Series: | Journal of Rock Mechanics and Geotechnical Engineering |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1674775522001664 |