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
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