A Comparison of the Performance of Supervised Learning Algorithms for Solar Power Prediction

A Comparison of the Performance of Supervised Learning Algorithms for Solar Power Prediction

Science seeks strategies to mitigate global warming and reduce the negative impacts of the long-term use of fossil fuels for power generation. In this sense, implementing and promoting renewable energy in different ways becomes one of the most effective solutions. The inaccuracy in the prediction of...

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Bibliographic Details
Main Authors: Leidy Gutiérrez, Julian Patiño, Eduardo Duque-Grisales
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Energies
Subjects:
photovoltaic systems
machine learning
supervised learning
prediction
artificial neural networks
k-nearest neighbors
Online Access:https://www.mdpi.com/1996-1073/14/15/4424

Internet

https://www.mdpi.com/1996-1073/14/15/4424

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