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Prediction and analysis of chaotic time series on the basis of support vector

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3 Author(s)
Li Tianliang ; The Engineering Inst., Air Force Engineering Univ., Xi'an 710038, P. R. China ; He Liming ; Li Haipeng

Based on discussion on the theories of support vector machines (SVM), an one-step prediction model for time series prediction is presented, wherein the chaos theory is incorporated. Chaotic character of the time series is taken into account in the prediction procedure; parameters of reconstruction-delay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neighbor method, respectively. Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series.

Published in:

Journal of Systems Engineering and Electronics  (Volume:19 ,  Issue: 4 )