DocumentCode
3022776
Title
Network traffic prediction based on BPNN optimized by self-adaptive immune genetic algorithm
Author
Shanying Cheng ; Xuemei Zhou
Author_Institution
Coll. of Math & Comput., Jiangxi Sci. & Technol. Normal Univ., Nanchang, China
fYear
2013
fDate
20-22 Dec. 2013
Firstpage
1030
Lastpage
1033
Abstract
In order to improve the prediction accuracy of the network traffic, aiming at the problem that the BP neural network prediction of the network traffic falls into local optimum easily, a new network traffic prediction method based on BPNN optimized by self-adaptive immune genetic algorithm is proposed. The proposed method is validated through the simulation experiment. The result analysis shows that it has higher prediction precision, which can provide an important theoretical basis for the prediction of the network traffic.
Keywords
backpropagation; genetic algorithms; neural nets; telecommunication network management; telecommunication traffic; BP neural network prediction; BPNN optimization; network traffic prediction method; self-adaptive immune genetic algorithm; Analytical models; Computers; Genetic algorithms; Neural networks; Prediction algorithms; Predictive models; Telecommunication traffic; BP neural network; network traffic prediction; self-adaptive immune genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location
Shengyang
Print_ISBN
978-1-4799-2564-3
Type
conf
DOI
10.1109/MEC.2013.6885213
Filename
6885213
Link To Document