Selection of Reconstruction Variables and Parameters in the Phase Space Reconstruction on Genetic Algorithm

Aimed at solving the interdependences among reconstruction variables and their parameters, this paper adopted genetic algorithm to determine reconstruction variables and parameters in the phase-space reconstruction of multivariate time series simultaneously. First, the process and method of phase-sp...

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Hauptverfasser: Hui Tao, Xiao-Ping Ma, Mei-Ying Qiao
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Aimed at solving the interdependences among reconstruction variables and their parameters, this paper adopted genetic algorithm to determine reconstruction variables and parameters in the phase-space reconstruction of multivariate time series simultaneously. First, the process and method of phase-space reconstruction of multivariate time series are introduced. Then the theory of genetic algorithm to select reconstruction variables and parameters is given that chromosome coding is binary code string of multi-parameters cascade, fitness function is average prediction error function and the optimal reconstruction variables and parameters combination is obtained through genetic operation. Finally, in Matlab2009b environment, the algorithm is applied to two examples. Simulation results show the algorithm can overcome the defect of determine reconstruction variables and parameters in isolation, and lay a good foundation for chaotic time series analysis and prediction.
DOI:10.1109/IWCFTA.2011.88