四川环境2023，Vol.42Issue(6)：24-30,7.DOI:10.14034/j.cnki.schj.2023.06.004
基于RFE-RF模型的太原市PM2.5浓度预测研究
Study on PM2.5 Concentration Prediction Based on REF-RF Model
摘要
Abstract
In order to make better use of the high altitude meteorological elements,the machine learning method is used to predict the concentration of PM25 in Taiyuan City.In this paper,the ambient air quality data of Taiyuan from 2015 to 2018 and the NCEP reanalysis data were used,the PM2.5 concentration of air pollutants was used as the label,according to the RFE characteristics selecting result,the prediction factors that are most conducive to improving the performance of the model were used as the input,the random forest regression model was selected for prediction,and three comparative models were constructed to further verify the prediction accuracy of the RF model.The results showed that the MAE,MAPE and RMSE of RF model were 17.19,38.17 and 26.0,respectively,which were reduced by 7.7％,5.1％and 2.7％respectively compared with Lasso model.Compared with SVM prediction model,MAE,MAPE and RMSE decreased by 23.1％,15.3％and 29.9％respectively.Compared with KNN prediction model,the MAE,MAPE and RMSE of RF model decreased by 17.2％,19.8％and 15.2％respectively.The RF model has good prediction effect,with R2 reaching 0.71.The correlation coefficients between the predicted values of the four models and the measured values were 0.76,0.78,0.82 and 0.84 respectively.The prediction effect of the RF model is better than that of Lasso model,KNN model and SVM model.By selecting the best RF prediction model and applying it to the daily ambient air quality prediction business,this paper will further improve the accuracy of the PM2 5 concentration prediction in Taiyuan City,and also provide an important scientific and technological means for strengthening the prevention and control of air pollution in Taiyuan City,and realizing the comprehensive environmental management and scientific decision-making.关键词
随机森林/NCEP/RFE特征选择/PM2.5浓度预测Key words
Random forest/NCEP/RFE feature selection/PM2.5 concentration prediction分类
资源环境引用本文复制引用
李明明,岳江,王雁,陈玲,杨爱琴..基于RFE-RF模型的太原市PM2.5浓度预测研究[J].四川环境,2023,42(6):24-30,7.基金项目
山西省科技厅面上自然基金项目"山西省重点区域重污染天气中长期预报技术研究"(201901D111465). （201901D111465）
