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http://dx.doi.org/10.5351/KJAS.2019.32.1.139

KTX passenger demand forecast with multiple intervention seasonal ARIMA models  

Cha, Hyoyoung (Department of Statistics, Hankuk University of Foreign Studies)
Oh, Yoonsik (Research Center, Korea Railroad)
Song, Jiwoo (Department of Statistics, Hankuk University of Foreign Studies)
Lee, Taewook (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
The Korean Journal of Applied Statistics / v.32, no.1, 2019 , pp. 139-148 More about this Journal
Abstract
This study proposed a multiple intervention time series model to predict KTX passenger demand. In order to revise the research of Kim and Kim (Korean Society for Railway, 14, 470-476, 2011) considering only the intervention of the second phase of Gyeong-bu before November of 2011, we adopted multiple intervention seasonal ARIMA models to model the time series data with additional interventions which occurred after November of 2011. Through the data analysis, it was confirmed that the effects of various interventions such as Gyeong-bu and Ho-nam 2 phase, outbreak of MERS and national holidays, which affected the KTX transportation demand, are successfully explained and the prediction accuracy could be quite improved significantly.
Keywords
ARIMA; forecasting; intervention; KTX; seasonal ARIMA;
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Times Cited By KSCI : 1  (Citation Analysis)
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