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Keywords: XGboost
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Journal Articles
Proceedings of the Institution of Civil Engineers - Water Management (2026) 179 (4): 161–176.
Published: 03 July 2026
... basin, India, evaluating their efficacy in handling rapid hydrological fluctuations. Three sophisticated machine learning models – random forest ( RF ), extreme gradient boosting (XGBoost) and long short-term memory ( LSTM ) networks – are employed to forecast streamflow across lead times ranging from 1...
