Study on Air Quality Forecast of Chuzhou Based on Random Forest Algorithm
Using the mass concentration of six air pollutants,AQI data,meteorological elements and ECM-WF numerical forecasts of Chuzhou from 2017 to 2019 as input parameters,a prediction model of pollutant mass concentration and AQI was built based on random forest algorithm,in which the forecast of AQI was divided into four models according to seasons.The results showed that O3 had the best predictive effect among the six pollu-tants,with a correlation coefficient of 0.84.The correlation coefficients of PM2.5,PM10,and NO2 were 0.76,0.72,and 0.72,respectively.The predictive effect of SO2 and CO was slightly poor.The TS score of 24-hour AQI forecast results based on seasonal models was 0.77,the false alarm rate(FAR)and underreporting rate(PO)were 15％and 12％,respectively,which were better than non-seasonal models.The TS score in spring and autumn reached 0.88 and 0.86,which were better than those in winter and summer.
Air qualityForecasting modelRandom forest algorithmChuzhou
万方数据
维普
