[HTML][HTML] Examining innovative unsupervised learning techniques for automated characterization of complex groundwater systems
MAA Mohammed, NP Szabó, R Kilik, P Szűcs - Results in Engineering, 2024 - Elsevier
This research proposes an innovative approach utilizing geophysical well logging data
analyzed with multiple machine learning (ML) methods including, self-organizing maps …
analyzed with multiple machine learning (ML) methods including, self-organizing maps …
Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters
MAA Mohammed, YG Flores, NP Szabó, P Szűcs - Scientific Reports, 2024 - nature.com
This research presents an unsupervised learning approach for interpreting well-log data to
characterize the hydrostratigraphical units within the Quaternary aquifer system in Debrecen …
characterize the hydrostratigraphical units within the Quaternary aquifer system in Debrecen …