Advanced Machine Learning Techniques to Improve Hydrological Prediction: A Comparative Analysis of Streamflow Prediction Models

Advanced Machine Learning Techniques to Improve Hydrological Prediction: A Comparative Analysis of Streamflow Prediction Models

The management of water resources depends heavily on hydrological prediction, and advances in machine learning (ML) present prospects for improving predictive modelling capabilities. This study investigates the use of a variety of widely used machine learning algorithms, such as CatBoost, ElasticNet...

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Bibliographic Details
Main Authors: Vijendra Kumar, Naresh Kedam, Kul Vaibhav Sharma, Darshan J. Mehta, Tommaso Caloiero
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Water
Subjects:
hydrological forecasting
machine learning
streamflow prediction
CatBoost
XGBoost
river inflow prediction
Online Access:https://www.mdpi.com/2073-4441/15/14/2572

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