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    Multi-Scale Variation Prediction of PM2.5 Concentration Based on a Monte Carlo Method

    Chen Ding1, Guizhi Wang1,*, Qi Liu2

    Journal on Big Data, Vol.1, No.2, pp. 55-69, 2019, DOI:10.32604/jbd.2019.06110

    Abstract Haze concentration prediction, especially PM2.5, has always been a significant focus of air quality research, which is necessary to start a deep study. Aimed at predicting the monthly average concentration of PM2.5 in Beijing, a novel method based on Monte Carlo model is conducted. In order to fully exploit the value of PM2.5 data, we take logarithmic processing of the original PM2.5 data and propose two different scales of the daily concentration and the daily chain development speed of PM2.5 respectively. The results show that these data are both approximately normal distribution. On the basis of the results, a Monte… More >

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