Litcius/Paper detail

Environmental Sensor-Less Hybrid Analytical-Machine Learning (ESHAML) framework for ultra-fast solar irradiance estimation in climate-sensitive real-time applications: experimental validation

Ambe Harrison, Wulfran Fendzi Mbasso, Idriss Dagal, Njimboh Henry Alombah, Pradeep Jangir, Saad F. Al‐Gahtani, Z. M. S. Elbarbary

2025Measurement7 citationsDOI

Topics & Concepts

IrradianceSolar irradianceEnvironmental scienceComputer scienceRemote sensingEstimationMeteorologyEngineeringSystems engineeringGeologyPhysicsOpticsSolar Radiation and PhotovoltaicsPhotovoltaic System Optimization TechniquesSolar Thermal and Photovoltaic Systems
Environmental Sensor-Less Hybrid Analytical-Machine Learning (ESHAML) framework for ultra-fast solar irradiance estimation in climate-sensitive real-time applications: experimental validation | Litcius