A Study on Ultrafine Dust Prediction Model Estimation Using ARIMA Model and Multiplicative SARIMA Model
Chang-Ho An,
Jae-Hyun Kim,
In-Kyu Song
Abstract:Ultrafine dust data has seasonality. Therefore, in this study, the ARIMA model and the multiplicative SARIMA model, which are time series modeling methods, were estimated in consideration of seasonality, and the accuracy of the estimated prediction model was proposed using the MAPE measure to propose an ultrafine dust prediction model. For the ultrafine dust data used for the estimation of the ARIMA model, a seasonally adjusted estimate using the decomposition method was used assuming a multiplicative model, a… Show more
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