Comparing numerical modelling, traditional machine learning and theory-guided machine learning in inverse modeling of groundwater dynamics: A first study case application

Published: 20 June 2023| Version 2 | DOI: 10.17632/87fkztgbbh.2
Contributor:
Adoubi Vincent De Paul ADOMBI

Description

The data, including processed input data and raw and processed results, algorithms, numerical model, and software used for the numerical modeling of this study are saved here. Important: The theory-guided machine learning code is inspired by that of Raissi et al., 2019 (https://doi.org/10.1016/j.jcp.2018.10.045).

Files

Steps to reproduce

All steps are explained in detail in the code files.

Institutions

Universite du Quebec a Chicoutimi

Categories

Groundwater, Machine Learning, Numerical Modeling

Licence