DocumentCode :
1986806
Title :
Supporting vector-machine prediction of network traffic
Author :
Wei, Xianmin
Author_Institution :
Comput. & Commun. Eng. Sch., Weifang Univ., Weifang, China
fYear :
2011
fDate :
16-18 Sept. 2011
Firstpage :
3203
Lastpage :
3206
Abstract :
In order to improve the accuracy of traffic forecasts, it´s important to apply the supporting vector regression in prediction of network traffic. This paper introduced key factors in supporting vector-machine regression modeling, and this model is applied to calculate the actual network traffic prediction, which compared with the BP neural network model. The results showed that supporting vector-machine regression model has better anti-noise ability, generalization ability and higher prediction accuracy, it can be a magnificent prediction of network traffic.
Keywords :
forecasting theory; generalisation (artificial intelligence); noise; regression analysis; support vector machines; telecommunication computing; telecommunication traffic; anti-noise ability; generalization ability; network traffic prediction; supporting vector machine prediction; supporting vector regression; traffic forecast accuracy; vector-machine regression modeling; Accuracy; Data models; Kernel; Mathematical model; Predictive models; Support vector machines; Training; BP neural network; flow prediction; regression; supporingt vector-machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
Type :
conf
DOI :
10.1109/ICECENG.2011.6057683
Filename :
6057683
Link To Document :
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