In recent years, the causes, prevention and control methods and prediction system of continuous haze weather have become the focus of social research.Taking the meteorological observation data of Hebei province as an example, this paper studies the influencing factors of continuous haze weather.Firstly, the improved TOPSIS algorithm is used to preprocess the data. Then, it combines the data mining methods such as hierarchical analysis and grey correlation analysis to carry out modeling analysis, and it is concluded that the particulate matter in the pollution source has the greatest impact on the haze weather. Moreover, as the aerodynamics factor affects the diffusion and aggregation of the haze pollution source, it is found that it has a linear influence on the formation of haze weather.Finally, through the current meteorological observation data, BP neural network is used to predict haze weather changes.A large number of experimental results show that, on the premise of allowing a certain error rate, the prediction effect of the BP neural network model is relatively accurate, and it also indicates that the formation of haze weather is closely related to the air quality index factor and meteorological index factor.
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