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    ARTICLE

    Predicting Concentration of PM10 Using Optimal Parameters of Deep Neural Network

    Byoung-Doo Oha,b, Hye-Jeong Songa,b, Jong-Dae Kima,b, Chan-Young Parka,b, Yu-Seop Kima,b

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 343-350, 2019, DOI:10.31209/2019.100000095

    Abstract Accurate prediction of fine dust (PM10) concentration is currently recognized as an important problem in East Asia. In this paper, we try to predict the concentration of PM10 using Deep Neural Network (DNN). Meteorological factors, yellow dust (sand), fog, and PM10 are used as input data. We test two cases. The first case predicts the concentration of PM10 on the next day using the day’s weather forecast data. The second case predicts the concentration of PM10 on the next day using the previous day’s data. Based on this, we compare the various performance results from More >

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