AI-Enabled Solar Radiation Prediction for Efficient Greenhouses

Accurate prediction of solar radiation is at the heart of Controlled Environment Agriculture (CEA) initiatives. This study aims to investigate the key variables that influence the predictive accuracy of Machine Learning(ML)-driven solar radiation forecasts. We also aim to investigate how effectively can these variables be used to build parsimonious, interpretable ML models for predicting solar radiation.