A Machine Learning Approach for Risk Assessment of Fluoride Contamination in Groundwater
Abstract
This dataset contains anonymized hydrochemical and fluoride concentration data (n = 87) collected from groundwater sources . The dataset includes physicochemical parameters used for hydrogeochemical analysis and machine learning modelling. Geographic coordinates have been removed to ensure location privacy. The dataset supports the results presented in the associated manuscript.
Fields of Study & Subjects
Fluoride Effects and Removal
Water Quality and Pollution Assessment
Hydrological Forecasting Using AI
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 February 2026
- Language
- EN
- Document type
- Dataset