Effective Prediction of Global Solar Radiation Using Machine Learning Algorithms and Satellite Images
Author:
Affiliation:
1. Université Paris-Saclay, Sorbonne Université,LATMOS/IPSL, UVSQ,Guyancourt,France,78280
2. Centre de Devellopement des Energies Renouvelables, CDER,Unité de Recherche Appliquée en Energies Renouvelables, URAER,Ghardaïa,Algeria,47133
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10537232/10537239/10537514.pdf?arnumber=10537514
Reference12 articles.
1. A state of art review on estimation of solar radiation with various models
2. A comprehensive review of hybrid models for solar radiation forecasting
3. Study of Atmospheric Turbidity on Different Algerian Sites Using a Model and MSG Satellite Images
4. Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network coupled with wavelet transform
5. A new approach to forecast solar irradiances using WRF and libRadtran models, validated with MERRA-2 reanalysis data and pyranometer measures
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