• 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