Prediction of Internet Traffic Based on Elman Neural Network

被引：17
|
作者：
Wang Junsong [1 ]
Wang Jiukun [2 ]
Zeng Maohua [2 ]
Wang Junjie [2 ]
机构：
[1] Tianjin Univ Technol & Educ, Tianjin 300222, Peoples R China
[2] Dagang Oil Field, Tianjin 300280, Peoples R China
来源：
CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年
关键词：
Internet traffic; Elman Neural network; Modeling; Prediction;
D O I：
10.1109/CCDC.2009.5192639
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Predicting internet traffic is needed for effective dynamic bandwidth allocation and for quality-of-service (QoS) control strategies implemented at the network edges. In this paper, a method is presented to model and predict the internet traffic based on Elman neural network(Elman-NN). The traffic is viewed as a time series, which is nonlinear and variant functions. An Elman neural network is employed to model the relationship with a satisfactory accuracy, and the Elman NN-based traffic model is used to conduct prediction for the future traffic. The simulation results show that this method is feasible and efficient to model and predict the traffic.
引用
收藏
页码：1248 / +
页数：2
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