Water quality prediction: a data-driven approach exploiting advanced machine learning algorithms with data augmentation

Water quality prediction: a data-driven approach exploiting advanced machine learning algorithms with data augmentation

Water quality assessment plays a crucial role in various aspects, including human health, environmental impact, agricultural productivity, and industrial processes. Machine learning (ML) algorithms offer the ability to automate water quality evaluation and allow for effective and rapid assessment of...

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Detalles Bibliográficos
Autores principales: Karthick K, S. Krishnan, R. Manikandan
Formato: Artículo
Lenguaje:English
Publicado: IWA Publishing 2024-02-01
Colección:Journal of Water and Climate Change
Materias:
machine learning
principal component analysis (pca)
synthetic minority over-sampling technique (smote)
water quality
water quality classification
Acceso en línea:http://jwcc.iwaponline.com/content/15/2/431

Internet

http://jwcc.iwaponline.com/content/15/2/431

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