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A systematic review of machine learning models for groundwater level prediction

This study presents a comprehensive synthesis of machine learning (ML) techniques applied to groundwater level (GWL) prediction, focusing on model architectures, feature selection methods, hyperparameter tuning, optimization algorithms, and clustering techniques. A total of 223 peer-reviewed article...

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Guardado en:
Autores principales: Gilbert Jesse, Cyril D. Boateng, Jeffrey N.A. Aryee, Marian A. Osei, David D. Wemegah, Solomon S.R. Gidigasu, Akyana Britwum, Samuel K. Afful, Haoulata Touré, Vera Mensah, Prinsca Owusu-Afriyie
Formato: Artigo
Lenguaje:Inglês
Publicado: Elsevier 2025-12-01
Colección:Applied Computing and Geosciences
Materias:
Machine learning
Groundwater level prediction
PRISMA
ANN
Feature selection
Optimization
Acceso en línea:http://www.sciencedirect.com/science/article/pii/S2590197425000850
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