Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Study on Performance Analysis of Short Term Internet Traffic Forecasting Models

단기 측정 인터넷 트래픽 예측을 위한 모형 성능 비교 연구

  • Ha, M.H. (Department of Applied Statistics, Chung-Ang University) ;
  • Son, H.G. (Department of Applied Statistics, Chung-Ang University) ;
  • Kim, S. (Department of Applied Statistics, Chung-Ang University)
  • 하명호 (중앙대학교 응용통계학과) ;
  • 손흥구 (중앙대학교 응용통계학과) ;
  • 김삼용 (중앙대학교 응용통계학과)
  • Received : 2012.02.28
  • Accepted : 2012.03.29
  • Published : 2012.05.31
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Abstract

In this paper, we first the compare the performance of Holt-Winters, FSARIMA, AR-GARCH and Seasonal AR-GARCH models with in the short term based data. The results of the compared data show that the Holt-Winters model outperformed other models in terms of forecasting accuracy.

본 연구에서는 단기에 측정되는 트래픽 자료를 예측하기 위하여 Holt-Winters, Fractional Seasonal ARIMA, AR-GARCH, Seasonal AR-GARCH 모형을 사용하여 각 모형의 예측 성능을 비교하고자 한다. 예측에 이용된 시계열 모형에 대해 소개하고, 실제 트래픽 자료에 적용하여 트래픽 자료를 분석한 결과 Holt-Winters방법이 예측력 측면에서 가장 우수하였다.

Keywords

References

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