Predicting Beijing Air Quality Data Based on LSTM Method

This paper studies the air quality data of Beijing from 2018 to 2020. On the basis of the correlation analysis of pollutant concentration, the circular neural network model based on LSTM algorithm is built to realize the prediction of AQI of Beijing. The results show that AQI index has a high correlation with PM2.5 and PM10, but only has a low negative correlation with O3. The prediction model of recurrent neural network shows high prediction accuracy. The research in this paper is helpful to promote the application of recurrent neural network model in air quality data and time series data. Zeng Guojing | Jin Renhao "Predicting Beijing Air Quality Data Based on LSTM Method" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd40000.pdf Paper URL: https://www.ijtsrd.com/engineering/other/40000/predicting-beijing-air-quality-data-based-on-lstm-method/zeng-guojing