Urban air quality index is an important indicator that reflects the level of livability of urban environment,and the forecast of the urban air quality index can be an important reference for policy formulation.This paper selects the air quality index(AQI)of Yangzhou City from 2014 to 2022 for time series analysis,and uses the time series models including the autoregressive integral moving average model(ARIMA),the prophet model(Prophet),and the long short-term memory model(LSTM)in the field of artificial intelligence to analyze the periodicity,seasonality and trend characteristics of the air quality index in Yangzhou City,and to forecast the air quality index.The results show that the AI-based LSTM has a strong predictive power.
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