Interpretable Machine Learning and Uncertainty Quantification for Groundwater Pollution Assessment in an Arid Aquifer

Assessing groundwater pollution in arid regions remains challenging due to complex hydrogeochemical processes and the limited interpretability and uncertainty awareness of some predictive models. Effective groundwater quality assessment, therefore, requires models that combine accurate prediction wi...

Volledige beschrijving

Bibliografische gegevens

Hoofdauteurs:	Ali Aldrees, Abdulhayat M. Jibrin, Salisu Dan'Azumi, Sani I. Abba
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	IEEE 2026-01-01
Reeks:	IEEE Access
Onderwerpen:	Bayesian classification groundwater quality quantile regression forest SHAP analysis water pollution index
Online toegang:	https://ieeexplore.ieee.org/document/11482437/
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!