Prediction on the fluoride contamination in groundwater at the Datong Basin, Northern China: Comparison of random forest, logistic regression and artificial neural network

• Published in: Applied geochemistry Vol. 132; p. 105054
• Main Authors: Nafouanti, Mouigni Baraka, Li, Junxia, Mustapha, Nasiru Abba, Uwamungu, Placide, AL-Alimi, Dalal
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2021
• Subjects: Artificial neural network; basins; calcium; China; Fluoride; fluorides; geochemistry; Groundwater; groundwater contamination; hydrochemistry; Logistic regression; neural networks; prediction; Random forest; regression analysis; risk; water quality; China; Logistic regression; Random forest; Fluoride; Artificial neural network; Groundwater

Groundwater fluoride is posing a health risk to humans, and analyzing groundwater quality is time-wasting and expensive. Statistical methods provide a valuable approach to study the spatial distribution of groundwater fluoride. Random Forest (RF), Artificial Neural Network (ANN), and Logistic Regres...