The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Study on Demand Forecasting for KTX Passengers by using Time Series Models

시계열 모형을 이용한 KTX 여객 수요예측 연구

  • Kim, In-Joo (Department of Hotel Tourism Service, Dae-Duk College) ;
  • Sohn, Hueng-Goo (Department of Applied Statistics, Chung-Ang University) ;
  • Kim, Sahm (Department of Applied Statistics, Chung-Ang University)
  • 김인주 (대덕대학교 호텔서비스학과) ;
  • 손흥구 (중앙대학교 응용통계학과) ;
  • 김삼용 (중앙대학교 응용통계학과)
  • Received : 2014.11.18
  • Accepted : 2014.11.22
  • Published : 2014.12.31
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Abstract

Since the introduction of KTX (Korea Tranin eXpress) in Korea reilway market, number of passengers using KTX has been greatly increased in the market. Thus, demand forecasting for KTX passengers has been played a importantant role in the train operation and management. In this paper, we study several time series models and compare the models based on considering special days and others. We used the MAPE (Mean Absolute Percentage Errors) to compare the performance between the models and we showed that the Reg-AR-GARCH model outperformanced other models in short-term period such as one month. In the longer periods, the Reg-ARMA model showed best forecasting accuracy compared with other models.

KTX에 등장에 따라 국내 여객시장은 KTX 시장을 중심으로 변화가 이루어졌다. 이에 따라 KTX 이용 여객의 수요예측은 열차 운영에 있어서 매우 중대한 사안이다. 본 논문에서는 여러 시계열 모형의 비교를 통해 KTX 이용 여객의 수요와 연관이 있는 요일과 공휴일, 명절을 어떠한 형태로 고려할 것인지 연구하였다. 모형 간 예측력을 비교하기 위하여 Mean Absolute Percentage Errors (MAPE)를 사용하였으며, 1달간의 단기간 예측에 있어서 변동성을 고려해줄 수 있는 Reg-AR-GARCH 모형이 우수한 예측력을 나타냈으며, 1달을 초과한 기간의 예측에서는 Reg-ARMA 모형이 우수한 예측력을 나타냈다.

Keywords

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