• DocumentCode
    532206
  • Title

    A short-term prediction for QoS of Web Service based on RBF neural networks including an improved K-means algorithm

  • Author

    Zhang Jin-hong

  • Author_Institution
    Sch. of Software, Northeastern Univ., Shenyang, China
  • Volume
    5
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    The structure of RBF neural networks and an improved K-means algorithm will be introduced in the paper. Based on this, RBF neural networks is applied to predict the QoS of Web Service and the functions of the MATLAB toolbox are adopted to create a network model for QoS prediction. Finally the simulation experiments will prove that using RBF neural networks based on the improved K-means algorithm to predict the QoS of Web Service is effective and efficient.
  • Keywords
    Web services; mathematics computing; pattern clustering; quality of service; radial basis function networks; MATLAB toolbox; QoS; RBF neural networks; k-means algorithm improvement; short term prediction; web service; Annealing; Artificial neural networks; Computer languages; Improved K-Means Algorithm; QoS Prediction; QoS Weight; RBF Neural Networks; Web Service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5620138
  • Filename
    5620138