Hybrid deep learning CNN-LSTM model for forecasting direct normal irradiance: a study on solar potential in Ghardaia, Algeria

Abstract This paper provides an in-depth analysis and performance evaluation of four Solar Radiance (SR) prediction models. The prediction is ensured for a period ranging from a few hours to several days of the year. These models are derived from four machine learning methods, namely the Feed-forwar...

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Автори:	Boumediene Ladjal, Mohamed Nadour, Mohcene Bechouat, Nadji Hadroug, Moussa Sedraoui, Abdelaziz Rabehi, Mawloud Guermoui, Takele Ferede Agajie
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Nature Portfolio 2025-05-01
Серія:	Scientific Reports
Предмети:	Artificial neural networks Convolutional neural network Convolutional feed-forward back propagation Deep learning Feed-forward back propagation Long short-term memory
Онлайн доступ:	https://doi.org/10.1038/s41598-025-94239-z
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Hybrid deep learning CNN-LSTM model for forecasting direct normal irradiance: a study on solar potential in Ghardaia, Algeria

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