Bias correction of ERA5-Land temperature data using standalone and ensemble machine learning...

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Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018–May 2023)

M Niazkar, A Menapace, B Brentan, R Piraei… - … Modelling & Software, 2024 - Elsevier
Abstract Applications of Machine Learning methods make a paradigm shift in the domain of
water resources engineering. This study not only presents the story of emerging eXtreme …
Shrani Navedi Navedeno v 57 virih Sorodni članki Vse različice: 7
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Assessment of climate change impact on water resources using machine learning algorithms

M Niazkar, M Zakwan, MR Goodarzi… - Journal of Water and …, 2024 - iwaponline.com
Machine learning (ML) algorithms bring about a game changer tool in develo** estimation
models in various fields of research, including water resources and climate change. These …
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Estimating Colebrook-White Friction Factor Using Tree-Based Machine Learning Models

M Niazkar, A Menapace, M Righetti - International Symposium on Industrial …, 2024 - Springer
Colebrook-White friction factor is the common hydraulic roughness coefficient used in water
supply systems. Analysis, design, and management of water distribution networks basically …
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Using Tree-Based Machine Learning Models

MNA Menapace, M Righetti - Latest Advancements in …, 2024 - books.google.com
Colebrook-White friction factor is the common hydraulic roughness coefficient used in water
supply systems. Analysis, design, and management of water distribution networks basically …
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