ANALYSIS OF MEDIUM-AND LONG-TERM CHANGES IN SOLAR RADIATION BASED ON RANDOM FOREST MODEL
This paper presents a comprehensive analysis of long-term solar radiation trends and influencing factors in Ji'nan City,Shandong Province,based on multi-source radiation observations,using the random forest(RF)algorithm,seasonal autoregressive integrated moving average(SARIMA)model and characteristic importance.The results show that the RF model fits the monthly solar radiation better,with the coefficient of determination and the mean absolute percentage error of 0.92 and 9%,respectively,which are better than the SARIMA model.The monthly solar radiation in Ji'nan City and the surrounding area experiences the process of"darkening"to"brightening"from 1980 to 2020.The maximum temperature and sunshine hours are the main factors affecting the accuracy of the monthly variation of solar radiation,rainfall is an important cause of sudden changes in total monthly solar radiation,and SO2 and O3 among atmospheric pollutants have the greatest correlation with solar radiation.This paper is important for guiding the development of the solar energy industry and environmental management in Ji'nan.
solar radiationrandom forestfeature selectionSARIMA modelfitting analysis
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