Long-term AI prediction of ammonium levels in rivers using transformer and ensemble models

Long-term AI prediction of ammonium levels in rivers using transformer and ensemble models

This study provides a cutting-edge machine learning approach to forecast ammonium (NH4+) levels in River Lee London. Ammonium concentrations were predicted over several time intervals using a complete dataset that includes temperature, turbidity, chlorophyll, dissolved oxygen, conductivity, and pH....

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Bibliographic Details
Main Authors:	Ali J. Ali, Ashraf A. Ahmed
Format:	Article
Language:	English
Published:	Elsevier 2024-12-01
Series:	Cleaner Water
Subjects:	Transformer model Extreme gradient boosting Random forest regressor River ecosystem Toxicity Ammonium
Online Access:	http://www.sciencedirect.com/science/article/pii/S2950263224000498
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