Forecasting solar irradiation based on influencing factors determined by linear correlation and stepwise regression

Determination of the factors influencing solar irradiation plays an important role in the performance of a prediction model based on machine learning techniques. This study compared the results obtained using a linear correlation analysis and stepwise regression method to identify the key meteorological, weather, and radiation factors that significantly affect the solar irradiation on the following day, as well as the difference between the quantities of solar irradiation on the current day and following day. These factors were used to establish prediction models for the Qinghai–Tibet Plateau, which has a complex topography and weather caprices. The results indicated that the stepwise regression method was capable of screening more effective influencing factors and the corresponding predictive accuracy was acceptable even under the weather conditions of the plateau.