Prediction for Network traffic Based on Modified Elman Neural Network

被引：0
|
作者：
Wang, Xuqi [1 ]
Zhaor, Zongtao [2 ]
Zhang, Shanwen [1 ]
机构：
[1] Xijing Univ, Dept Engn Technol, Xian 710123, Peoples R China
[2] Second Artillery Engn Coll, Dept Comp Sci, Xian 710025, Peoples R China
来源：
INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4 | 2013年 / 241-244卷
关键词：
Modified Elman neural network; Network traffic; Modeling; network behavior;
D O I：
10.4028/www.scientific.net/AMM.241-244.3005
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A modified Elman neural network model for the network system is proposed which is nonlinear, multivariable and time-varying. The learning method based on seasonal periodicity is introduced into the model training. And the output traffic of the backbone network at a certain university is selected for the test. Experimental results show this model has better accuracy of prediction. Compared with traditional linear model, BP neural network model and normal Elman neural network model, it has higher accuracy and better adaptability. Finally, abnormal behavior of network traffic can be found on time through the test of adaptive boundary value. And it shows that the model is feasible and effective.
引用
收藏
页码：3005 / +
页数：2
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