Cubist Regression, Random Forest and Support Vector Regression for Solar Power Prediction

Cubist Regression, Random Forest and Support Vector Regression for Solar Power Prediction

At a time when the energy transition is inescapable and artificial intelligence is rapidly advancing in all directions, solar renewable energy output forecasting is becoming a popular concept, especially with the availability of large data sets and the critical requirement to forecast these energies...

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Bibliographic Details
Main Authors: Souhaila Chahboun, Mohamed Maaroufi
Format: Article
Language:English
Published: Renewable Energy Development Center (CDER) 2022-06-01
Series:Revue des Énergies Renouvelables
Subjects:
photovoltaic
machine learning
artificial intelligence
solar energy
prediction
Online Access:https://revue.cder.dz/index.php/rer/article/view/1040

Internet

https://revue.cder.dz/index.php/rer/article/view/1040

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