• DocumentCode
    2152817
  • Title

    The application of improved Empirical Mode Decomposition Algorithm algorithm to the intelligent mechanical ventilation bed

  • Author

    Li, Hua-lai ; Liu, Zai-wen ; Xu, Ji-ping ; Xiao-yi, Wang ; Xu, Yuan-da

  • Author_Institution
    Department of computer and information engineering, Beijing Technology and business university, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    4759
  • Lastpage
    4762
  • Abstract
    To forecast precisely the time series to the intelligent mechanical ventilation bed online, the improved Empirical Mode Decomposition Algorithm was introduced novel EMD algorithm (NEMD) was gotten in this paper by using piecewise power function to generate envelope curves and extending their end points. The improved EMD was utilized to decompose the de-noised data, Next, the BP Neural Network (NN) and Least Square Support Vector Machines (LSSVM) were used to predict the low frequency items and high frequency items of the decomposed sequence data. The modeling and simulation results indicate that the algorithm that the improved EMD algorithm was introduced in realized online can forecast the time series precisely.
  • Keywords
    Artificial neural networks; Computational modeling; Computer simulation; Computers; Prediction algorithms; Time series analysis; Ventilation; Empirical Mode Decomposition; Interpolation algorithm; Power function; neural network; time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5691441
  • Filename
    5691441