An Interpretable Machine Learning Model for Daily Global Solar Radiation Prediction

An Interpretable Machine Learning Model for Daily Global Solar Radiation Prediction

Machine learning (ML) models are commonly used in solar modeling due to their high predictive accuracy. However, the predictions of these models are difficult to explain and trust. This paper aims to demonstrate the utility of two interpretation techniques to explain and improve the predictions of M...

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Bibliographic Details
Main Authors: Mohamed Chaibi, EL Mahjoub Benghoulam, Lhoussaine Tarik, Mohamed Berrada, Abdellah El Hmaidi
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Energies
Subjects:
solar radiation
support-vector regression
light gradient boosting
multilayer perceptron
permutation feature importance
Shapley additive explanations
Online Access:https://www.mdpi.com/1996-1073/14/21/7367

Internet

https://www.mdpi.com/1996-1073/14/21/7367

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