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文章基本信息

  • 标题:Network Traffic Time Series Performance Analysis Using Statistical Methods
  • 本地全文:下载
  • 作者:Purnawansyah Purnawansyah ; Haviluddin Haviluddin ; Rayner Alfred
  • 期刊名称:Knowledge Engineering and Data Science
  • 印刷版ISSN:2597-4602
  • 电子版ISSN:2597-4637
  • 出版年度:2018
  • 卷号:1
  • 期号:1
  • 页码:1-7
  • DOI:10.17977/um018v1i12018p1-7
  • 出版社:Universitas Negeri Malang
  • 摘要:This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting.
  • 其他摘要:This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting.
  • 关键词:Decomposition;Winter’s exponential smoothing;ARIMA;Additive;Multiplicative
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