• DocumentCode
    1615789
  • Title

    Analysis and research of several network traffic prediction models

  • Author

    Xu Lan

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Bohai Univ., Jinzhou, China
  • fYear
    2013
  • Firstpage
    894
  • Lastpage
    899
  • Abstract
    There are many factors which affect the prediction of network traffic at present. The traditional network traffic prediction model has not met the needs of prediction. Therefore, many scholars have been researching on the area. This paper analyzed network traffic prediction models based on neural network by ant colony optimization algorithm, based on neural network by quantum particle swarm optimization algorithm, and based on neural network by genetic algorithm optimized; studied the forecasting process of these models; compared the forecasting performance of three models. And proposed view for study in the future.
  • Keywords
    ant colony optimisation; genetic algorithms; information networks; neural nets; particle swarm optimisation; ant colony optimization algorithm; forecasting process; genetic algorithm; network traffic prediction models; neural network; quantum particle swarm optimization algorithm; Decision support systems; Ant Colony Optimization Algorithm; Genetic Algorithm; Network Traffic; Neural Network; Prediction; Quantum-behaved Particle Swarm Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chinese Automation Congress (CAC), 2013
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-0332-0
  • Type

    conf

  • DOI
    10.1109/CAC.2013.6775859
  • Filename
    6775859