| Extending SC-PDSI-PM with neural network regression using GLDAS data and Permutation Feature Importance SG Ramirez, RC Hales, GP Williams, NL Jones Environmental Modelling & Software 157, 105475, 2022 | 29 | 2022 |
| Groundwater level data imputation using machine learning and remote earth observations using inductive bias SG Ramirez, GP Williams, NL Jones Remote Sensing 14 (21), 5509, 2022 | 10 | 2022 |
| Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning SG Ramirez, GP Williams, NL Jones, DP Ames, J Radebaugh Water 15 (6), 1236, 2023 | 6 | 2023 |
| Applied Machine Learning in Development of Geospatial Information Tools for Sustainable Groundwater Management SG Ramirez Brigham Young University, 2023 | 2 | 2023 |
| Groundwater Storage Loss in the Central Valley Analysis Using a Novel Method based on In Situ Data Compared to GRACE-Derived Data MD Stevens, SG Ramirez, EMH Martin, NL Jones, GP Williams, ... Environmental Modelling & Software, 106368, 2025 | | 2025 |
| A Machine Learning Approach for Identification of Low-Head Dams S Vinay, RH Hotchkiss, S Ramirez Water 15 (4), 676, 2023 | | 2023 |
| Using Remote Earth Observations and In Situ Observations to Impute Sparse Groundwater Data at Individual Wells with Machine Learning S Ramirez, GP Williams, N Jones AGU Fall Meeting Abstracts 2022, H22P-1055, 2022 | | 2022 |
| Extending SC-PDSI-PM with Regression Neural Networks using GLDAS and Permutation Feature Importance S Ramirez, R Hales, G Williams, N Jones AGU Fall Meeting Abstracts 2021, GC45B-0837, 2021 | | 2021 |
| Toward Using Empirical Mode Decomposition to Identify Anomalies in Stream Flow Data and Correlations with Other Environmental Data SG Ramirez Brigham Young University, 2019 | | 2019 |
Gustavious Paul WilliamsAssociate Professor of Civil and Construction Engineering, Brigham Young UniversityDirección de correo verificada de byu.edu