Predicting global horizontal irradiance using regression-based machine learning models in high-altitude environments

Global solar radiation is a fundamental component of the Earth's energy balance and plays a critical role in integrating renewable energy into electrical systems. However, its pronounced variability, particularly in high-altitude regions, constrains energy stability and complicates planning processe...

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Autores principales: Milton Edward Humpiri Flores, David Mamani-Pari, Danny Lévano Rodríguez, Roel Dante Gómez Apaza, Esteban Tocto-Cano, Ángel Rosendo Condori-Coaquira, Javier Linkolk López‐Gonzales
Formato: Artículo
Lenguaje:inglés
Publicado: 2026
Materias:
global radiation
solar irradiance forecasting
high-altitude environment
clearness index
data leakage
specific humidity
NASA POWER
random forest
gradient boosting
linear regression
polynomial regression
shallow neural networks
feature importance
SHAP
cloud processes
renewable energy integration
Solar Radiation and Photovoltaics
Solar Thermal and Photovoltaic Systems
Meteorological Phenomena and Simulations
Acceso en línea:Enlace permanente (DOI o Handle)
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