Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression

Accurate renewable energy forecasting is crucial for grid stability and efficient energy management. This study introduces a hybrid model that combines signal decomposition and artificial intelligence to enhance the prediction of solar radiation and wind speed. The framework uses a one-stage decompo...

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Bibliographic Details
Main Authors:	Nahed Zemouri, Hatem Mezaache, Zakaria Zemali, Fabio La Foresta, Mario Versaci, Giovanni Angiulli
Format:	Article
Language:	English
Published:	MDPI AG 2025-06-01
Series:	Energies
Subjects:	solar radiation wind speed hybrid deep learning forecasting least-squares regression hybrid model
Online Access:	https://www.mdpi.com/1996-1073/18/11/2942
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Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression

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