• DocumentCode
    2014326
  • Title

    Study on prediction modeling of the artificial neural network from the combination of multivariate analysis and mean generation function

  • Author

    Long, Jin ; Ying, Luo ; Yonghua, Li

  • Author_Institution
    Guangxi Meteorological Bur., Nanning, China
  • Volume
    3
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    2440
  • Abstract
    A mixed prediction model involving a significant period of a predictand the physical factors influencing the change of predictand is built based on an artificial neural network from the combination of multivariate analysis and mean generation function. The new model is found to have a higher predicative accuracy (due mainly to the reasonable analysis for prediction method), when compared to results from multivariate statistical model or mean generating function prediction model.
  • Keywords
    geophysics computing; meteorology; modelling; neural nets; statistical analysis; artificial neural network; mean generation function; mixed prediction model; multivariate analysis; predicative accuracy; predictand; prediction modeling; Artificial neural networks; Automation; Intelligent control; Meteorology; Prediction methods; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
  • Print_ISBN
    0-7803-7268-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2002.1021530
  • Filename
    1021530