The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Time Series Models for Performance Evaluation of Network Traffic Forecasting

시계열 모형을 이용한 통신망 트래픽 예측 기법연구

  • Kim, S. (Department of Statistics, Chung-Ang University)
  • Published : 2007.07.31
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Abstract

The time series models have been used to analyze and predict the network traffic. In this paper, we compare the performance of the time series models for prediction of network traffic. The feasibility study showed that a class of nonlinear time series models can be outperformed than the linear time series models to predict the network traffic.

시계열 모형은 통신망 트래픽의 예측과 분석에 유용하게 쓰여 왔다. 본 논문에서는 통신망 트래픽의 예측을 위하여 다양한 시계열 모형을 소개하고 성능평가를 하고자 한다. 이를 위하여 실제 통신망 트래픽 자료에 선형 및 비선형 시계열모형을 적합 시키고 비선형 시계열모형이 선형 시계열 모형보다 예측의 정확도가 우수함을 보이고자 한다.

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References

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  2. A Study on the Short Term Internet Traffic Forecasting Models on Long-Memory and Heteroscedasticity vol.26, pp.6, 2013, https://doi.org/10.5351/KJAS.2013.26.6.1053
  3. A Study on Internet Traffic Forecasting by Combined Forecasts vol.28, pp.6, 2015, https://doi.org/10.5351/KJAS.2015.28.6.1235