DocumentCode
604504
Title
A network traffic prediction model based on recurrent wavelet neural network
Author
Run Zhang ; Yinping Chai ; Xing-an Fu
Author_Institution
Dept. of Math., Chuxiong normal Univ., Chuxiong, China
fYear
2012
fDate
29-31 Dec. 2012
Firstpage
1630
Lastpage
1633
Abstract
The network traffic prediction model is the foundation of network performance analysis and designing. The traditional traffic models have the weakness of low-level efficiency. The recurrent wavelet neural network(RWNN) based on EIman network was proposed in the paper, and the dynamic gradient descent algorithm of RWNN was given, and could be used in the network traffic prediction. Experimental results show that the network traffic prediction model based on RWNN is feasible and effective.
Keywords
Internet; computer network management; gradient methods; recurrent neural nets; wavelet transforms; EIman network; Internet traffic prediction; RWNN; dynamic gradient descent algorithm; network performance analysis; network performance design; network traffic prediction model; recurrent wavelet neural network; TD-ERCS; encryption algorithm; seed parameters;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4673-2963-7
Type
conf
DOI
10.1109/ICCSNT.2012.6526232
Filename
6526232
Link To Document