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The air pollution of Beijing-Tianjin-Hebei region in China becomes increasingly serious. Focus on the air quality management of Beijing-Tianjin-Hebei region, this paper proposes a method based on SVM algorithm and multivariate linear regression to the prediction and evaluation of air quality. First, it builds the evaluation metrics based on the weather factors, the correlation of neighbor cities, and their combination. Furthermore, it applies the SVM algorithm to the classification and prediction of air quality of Beijing-Tianjin-Hebei region. By the application of multivariate linear regression method, the weather factor with no significant effect on air quality is removed to save the cost of calculation. Finally, the experimental results show that the method based on the combination of weather factors and correlation of neighbor cities is better than the other two methods. We draw the conclusion that the method is feasible and effective. Keywords—support vector machine (SVM); data mining; multivariate linear regression; air quality index (AQI)

Research on Air Quality of Beijing-Tianjin-Hebei Region based on SVM and Regression Analysis