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With the development of China’s economy, the environmental quality is deteriorating, and the problem of air pollution has become particularly prominent. People’s high quality of life is closely related to air pollution. Air quality information is information that people will inevitably pay attention to every day. Therefore, research on air quality prediction methods is of very practical significance for revealing the changing laws of urban air quality, grasping air quality, and guiding people’s travel and lifestyle. This paper takes Beijing’s PM2.5 pollution as an example to study air quality prediction methods. Firstly, analyzing the correlation between air pollutant concentration and meteorological factors, establishing a GA-BP pollutant concentration prediction model with meteorological factors and historical pollutant concentration as input factors, and verifying GA-BP through a comparison experiment with the standard BP prediction model. Subsequently, based on the GA-BP pollutant concentration prediction model, a progressive prediction method was proposed, and the concentration prediction process of PM2.5 was used to predict the concentration of other five air pollutants. Based on the prediction of pollutant concentration, it refers to the calculation method of the air quality index to predict the AQI and AQI level. Comparing the predicted level with the actual level, verifying the feasibility and accuracy of the prediction method, establishing an air quality prediction system with GA-BP hybrid algorithm as the core.
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