• DocumentCode
    2948878
  • Title

    Determining Parameters in the Phase-Space Reconstruction of Multivariate Time Series on Genetic Algorithm

  • Author

    Tao, Hui ; Ma, Xiao-Ping ; Qiao, Mei-Ying

  • Author_Institution
    Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2011
  • fDate
    20-21 Aug. 2011
  • Firstpage
    81
  • Lastpage
    84
  • Abstract
    Based the principle of minimizing average prediction error, in this paper genetic algorithm is adopted to determine parameters in the phase-space reconstruction of multivariate time series. First, the methods of phase-space reconstruction and multivariate time series prediction are introduced. Then the theory of genetic algorithm to select reconstruction parameters is given that chromosome coding is multi-parameters cascade binary string, fitness is average prediction error function and the optimal parameters combination is obtained through genetic operation. Finally, in Matlab2009b simulation environment, the algorithm is applied to confirm embedding dimensions and time-delays of Rossler coupling system, and the results show that the algorithm has high prediction precision and rapid calculating speed.
  • Keywords
    delays; genetic algorithms; parameter estimation; phase space methods; time series; Matlab2009b simulation; Rossler coupling system; average prediction error function; average prediction error minimization; chromosome coding; genetic algorithm; multiparameters cascade binary string; multivariate time series prediction; parameter determination; phase-space reconstruction; time-delay; Biological cells; Chaos; Couplings; Encoding; Genetic algorithms; Prediction algorithms; Time series analysis; Embedding dimension; Genetic algorithm; Multivariate time series; Phase-space reconstruction; Time-delay;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence Science and Information Engineering (ISIE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4577-0960-9
  • Electronic_ISBN
    978-0-7695-4480-9
  • Type

    conf

  • DOI
    10.1109/ISIE.2011.122
  • Filename
    5997382