Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data

Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data

Sub-surface soil hydrological characterization is one of the challenging tasks for engineers and soil scientists, especially the complex hydrological processes that combine key variables such as soil moisture, matric suction, and soil temperature. The ability to infer these variables through a singu...

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Bibliographic Details
Main Authors: Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Geotechnics
Subjects:
electrical resistivity
ET cover
machine learning
decision tree
random forest
support vector machine
Online Access:https://www.mdpi.com/2673-7094/5/1/5
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