Comparing numerical modelling, traditional machine learning and theory-guided machine learning in inverse modeling of groundwater dynamics: A first study case application
Published: 28 May 2024| Version 3 | DOI: 10.17632/87fkztgbbh.3
Contributor:
Adoubi Vincent De Paul ADOMBIDescription
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. The paper can be accessed here: https://doi.org/10.1016/j.jhydrol.2022.128600. 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