Advanced predictive modelling of electrical resistivity for geotechnical and geo-environmental applications using machine learning techniques

• Published in: Journal of applied geophysics Vol. 231; p. 105557
• Main Authors: Kundu, Soumitra Kumar, Dey, Ashim Kanti, Sapkota, Sanjog Chhetri, Debnath, Prasenjit, Saha, Prasenjit, Ray, Arunava, Khandelwal, Manoj
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2024
• Subjects: Artificial neural networks; Electrical resistivity; Extreme Gradient Boosting; Support vector regression; Support vector regression; Extreme Gradient Boosting; Electrical resistivity; Artificial neural networks

Electrical Resistivity (ER) is one of the best geophysical methods for subsurface investigation, especially for geotechnical and geo-environmental studies. Being non-invasive, economical and rapid, this method is highly preferable to geotechnical engineers for continuous evaluation of soil propertie...