PM2.5 Concentration Prediction Model Based on Prophet-LightGBM
In recent years,the issue of PM2.5 pollution has become increasingly prominent,causing serious impacts on people's physical health and environmental quality.Therefore,establishing an accurate PM2.5 concentration prediction model is of great significance for pollu-tion prevention and air quality management.A combined model combining Prophet model and LightGBM model is proposed to address the non-linear,high noise,and non-stationary characteristics of PM2.5 time series.In order to verify the effectiveness of the model,the Prophet Light-GBM model and four other prediction models were compared and analyzed with PM2.5 concentration data in Lanzhou City as an example,as well as their prediction effects in different seasons.The results showed that the Prophet LightGBM model was more accurate in predicting the trend of PM2.5 concentration changes compared to the comparative model.The RMSE value reached 6.557,the MAE value reached 4.543,and the MAPE value reached 14.344%.It showed better performance in predicting accuracy and stability in summer and autumn,with the RMSE value reaching 3.155,the MAE value reaching 2.169,and the MAPE value reaching 9.4%when the RMSE value was optimal.
PM2.5 concentration predictionProphet modelLightGBM modelcomposite model
国家科技期刊平台
NSTL
万方数据
