Lanzhou City Based On EEMD-LSTM-ARIMA Air Quality Prediction Study

With the rapid and continuous economic development,the large amount of energy demand and over-exploitation has caused adverse effects such as the destruction of vegetation and increased emissions of exhaust gases.This directly affects the excellent degree of air quality and thus the health of the people.And as an industrial city surrounded by mountains,Lanzhou City has difficulties in dissipating atmospheric pollutants,which causes a decline in air quality.In this paper,we use the data of air pollutant concentration in Lanzhou City from 2014 to 2020 to explore the change pattern of air quality in Lanzhou City and analyze the characteristics of air quality in Lanzhou City to provide conditions for the subsequent air quality index prediction.Based on the comparative analysis of the effects of several models,a combined model is selected for AQI air quality index prediction,which effectively improves the prediction accuracy.The main results are as follows: firstly,the air quality data of Lanzhou City from2014 to 2020 were divided into annual,quarterly and monthly,and the change pattern of air quality in Lanzhou City was explored separately.It was found that the air quality of Lanzhou City showed cyclical fluctuations with more obvious quarterly characteristics,low air pollution level in summer and high pollutant level in winter.Secondly,each single model was selected for comparison,and the single model with higher accuracy after comparison was put into the establishment of the combined model.Finally,the LSTM,EEMD-LSTM,and EEMD-LSTM-ARIMA models are used to predict the AQI index,and the prediction results of each model are compared,and finally the EEMD-LSTM-ARIMA model has the most accurate prediction of the AQI index.The combined model was finally proved to provide the corresponding basis for air quality prediction.