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인터넷 트래픽 예측 모형 성능 분석 연구Performance Analysis of Internet Traffic Forecasting Model

Authors
김삼용하명호정재윤
Issue Date
Apr-2011
Publisher
한국통계학회
Keywords
트래픽; 장기기억; Holt-Winters; FARIMA; AR-GARCH; Traffic; long memory; Holt-Winters; FARIMA; AR-GARCH
Citation
응용통계연구, v.24, no.2, pp 307 - 313
Pages
7
Journal Title
응용통계연구
Volume
24
Number
2
Start Page
307
End Page
313
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/33908
ISSN
1225-066X
Abstract
본 연구에서는 인터넷 트래픽 자료를 예측하는데 사용되는 Holt-Winters, FARIMA, AR-GARCH 모형을 트래픽 예측에 적용하여 각 모형을 성능을 비교하고자 한다. 각 시계열 모형에 대해 소개하고, 트래픽 자료의 특성인 장기기억 특성을 설명하는데 적합한 모형을 알아보기 위해 실제 트래픽 자료에 적용하여 예측 성능을 비교하였다.
In this paper, we compare performance of three models. The Holt-Winters, FARIMA and ARGARCH models, are used in predicting internet traffic data for analysis of traffic characteristics. We first introduce the time series models and apply them to real traffic data to forecast. Finally, we examine which model is the most suitable for explaining the long memory, the characteristics of the traffic material, and compare the respective prediction performance of the models.
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