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Comparative Analysis of Machine Learning Algorithms for Water Quality Prediction

This study aims to identify the influential parameters and heavy metals in water and assess the water quality classification at the Alpine glacial lakes and rivers in three districts of Pakistan. For this purpose, nine water quality parameters (Cd, Cr, Pb, Ni, Fe, As, and TDS) in mg/L, pH, Ec µS/Cm...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Muhammad Akhlaq, Asad Ellahi, Rizwan Niaz, Mohsin Khan, Saad Sh. Sammen, Miklas Scholz
Format: Artigo
Sprache:Inglês
Veröffentlicht: Stockholm University Press 2024-07-01
Schriftenreihe:Tellus: Series A, Dynamic Meteorology and Oceanography
Schlagworte:
heavy metals
glacial lakes
river contamination
boruta algorithm
supervised machine learning
Online-Zugang:https://account.a.tellusjournals.se/index.php/su-j-tadmo/article/view/4069
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