This study demonstrates the effectiveness of various machine learning algorithms in predicting solar radiation using meteorological data.
This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimization (IPSO)
by Z Allal · 2024 · Cited by 43 — This paper explores solar irradiance forecasting as a machine-learning problem. We utilize data from Izmir, Turkey, over a period spanning three years.
by L Wang · 2021 · Cited by 26 — This paper proposes a comprehensive application of machine learning techniques for short-term solar radiation prediction. Firstly, aiming at the missing entries
This study presents a novel long-term solar irradiance forecasting approach, utilizing meteorological data from the National Renewable Energy Laboratory
by L Huang · 2021 · Cited by 206 — We constructed 12 machine learning models to predict and compare daily and monthly values of solar radiation and a stacking model using the best of these
55 4 Conclusion & Future Directions 4.1 Conclusion The results presented in this thesis indicate that properly-chosen machine learning techniques can be used to generate models of solar irradiance, and there are several techniques by which the accuracy of such models may be improved. Chapter 2 affirms previous findings from the literature which demonstrate the importance of incorporating predictive data such as weather forecasts in models of irradiance for timeframes between 1 and 24 hours. The results reported in this thesis suggest that machine learning techniques such as random forest are well-suited to build accurate models of future irradiance, particularly when predictive data such as numerical weather predictions are available.
by WF Lee · 2025 · Cited by 1 — The developed ML model significantly enhanced the accuracy and stability of 1-h solar radiation forecasts compared with the HRRR model, benefiting high tunnel