A network traffic prediction model based on recurrent wavelet neural network

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 E Iman network was proposed in the paper, and the dynamic gradient desce...

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Bibliographic Details
Published in:2012 2nd International Conference on Computer Science and Network Technology pp. 1630 - 1633
Main Authors: Zhang, Kun, Chai, Yinping, Fu, Xing-an
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2012
Subjects:
Artificial neural networks
Biological neural networks
encryption algorithm
Heuristic algorithms
Mathematical models
Neurons
Predictive models
seed parameters
TD-ERCS
Telecommunication traffic
Time measurement
Time series analysis
Training
ISBN:1467329630, 9781467329637
Online Access:Get full text
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Summary: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 E Iman 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.
ISBN:1467329630
9781467329637
DOI:10.1109/ICCSNT.2012.6526232