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
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;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526232
