Future Estimation of Hydrometeorological Variables Using Machine Learning Techniques: A Comparative Approach
Jean Firmino Cardoso,
Erickson Johny Galindo da Silva,
Ialy Rayane de Aguiar Costa
et al.
Abstract:Objective: The objective of the research was to analyze and compare different machine learning models to identify which technique presents the best performance in predicting hydrometeorological variables.
Theoretical Framework: This section presents the main concepts that underpin the work. Machine learning techniques such as support vector machines, decision trees, random forests, artificial neural networks, and gradient boosting are presented, providing a solid foundation for understanding the context of… Show more
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