Network Traffic Prediction Based on Wavelet Transform and Season ARIMA Model

被引：0

作者：

Wei, Yongtao ^{[1
]}

Wang, Jinkuan ^{[1
]}

Wang, Cuirong ^{[1
]}

机构：

[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT III | 2011年 / 6677卷

关键词：

Network Traffic; Wavelet; Season ARIMA;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To deal with the characteristic of network traffic, a prediction algorithm based on wavelet transform and Season ARIMA model is introduced in this paper. The complex correlation structure of the network history traffic is exploited with wavelet method For the traffic series under different time scale, self-similarity is analyzed and different prediction model is selected for predicting. The result series is reconstructed with wavelet method. Simulation results show that the proposed method can achieve higher prediction accuracy rather than single prediction model.

引用

页码：152 / 159

页数：8

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