Application of machine learning to fill in the missing monitoring data of air quality

In this paper, three machine learning models have been applied to predict and fill in the missing monitoring data of air quality for Gia Lam and Nha Trang stations in Hanoi and Khanh Hoa respectively, including Autoregressive Moving Average (ARMA), Artificial Neural Network (ANN), and Support Vector Regression (SVR). Two air pollutants being NO2 and PM10 were selected for this study.
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Application of machine learning to fill in the missing monitoring data of air quality