• DocumentCode
    2477293
  • Title

    A prediction model based on neural network and fuzzy Markov chain

  • Author

    Liu, Jia ; Li, Shunxiang ; Jia, Shusheng

  • Author_Institution
    Key Lab. of Automobile Mater., Jilin Univ., Changchun
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    790
  • Lastpage
    793
  • Abstract
    In order to solve the problem of random and fluctuation of experiment errors and predication errors of neural network, a neural network model modified by a fuzzy Markov chain was introduced, When neural network was used to predict, the prediction errors between actual value and output value of the network were distributed randomly. That can be simulated by a Markov chain. According to the forecasting property of Markov chain, the prediction errors of neural network can be modified by the fuzzy Markov chain. The addition of fuzzy Markov chain to ANN method can prominently improve the prediction quality. This model was applied to analysis the properties of nano-composite materials. And the result showed it was effective and better than neural network model.
  • Keywords
    Markov processes; forecasting theory; neural nets; prediction theory; forecasting property; fuzzy Markov chain; neural network; prediction errors; prediction model; Artificial neural networks; Automation; Error correction; Fluctuations; Fuzzy control; Fuzzy neural networks; Intelligent control; Nanostructured materials; Neural networks; Predictive models; BP neural network; Markov chain; Nano-composite materials; Prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593023
  • Filename
    4593023