• DocumentCode
    3075933
  • Title

    Based on Two Swarm Optimized Algorithm of Neural Network to Prediction the Switch´s Traffic of Coal

  • Author

    Shao, Xiao-qiang

  • Author_Institution
    Sch. of Electr. & Control Eng., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
  • fYear
    2011
  • fDate
    16-17 July 2011
  • Firstpage
    299
  • Lastpage
    302
  • Abstract
    Coal accurately predict multi-channel network traffic monitoring network for transmission to enhance and improve the QoS is very important, the characteristics of coalmine monitoring network, the first neural network model was constructed, followed by the ant colony algorithm, on the number of iterations, time, number of parameters such as ants Set, then uses the number of Particle swarm optimization particles, particles and other parameters set the location to complete the layers of neural network weights optimization, simulation by examples of its accuracy.
  • Keywords
    coal; mining industry; neural nets; particle swarm optimisation; process monitoring; quality of service; telecommunication congestion control; telecommunication traffic; QoS; ant colony algorithm; coal mine monitoring network; multichannel network traffic monitoring; neural network; particle swarm optimization; swarm optimized algorithm; switch traffic; Fuzzy neural networks; Mathematical model; Monitoring; Optimization; Particle swarm optimization; Predictive models; Training; Coal; Particle swarm optimization; ant colony algorithm; network traffic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Society (ISCCS), 2011 International Symposium on
  • Conference_Location
    Kota Kinabalu
  • Print_ISBN
    978-1-4577-0644-8
  • Type

    conf

  • DOI
    10.1109/ISCCS.2011.87
  • Filename
    6004445