A generic framework for geotechnical subsurface modeling with machine learning

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...

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Bibliographic Details
Main Authors: Jiawei Xie, Jinsong Huang, Cheng Zeng, Shan Huang, Glen J. Burton
Format: Article
Language:English
Published: Elsevier 2022-10-01
Series:Journal of Rock Mechanics and Geotechnical Engineering
Subjects:
Site investigation
Machine learning (ML)
Spatial interpolation
Geotechnical distance fields (GDFs)
Tree-based models
Online Access:http://www.sciencedirect.com/science/article/pii/S1674775522001664

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http://www.sciencedirect.com/science/article/pii/S1674775522001664

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