Predictability of Iteration Method for Chaotic Time Series

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概要

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• The approximation expression about error accumulation of a long-term prediction is derived. By analyzing this formula, we find that the factors that can affect the long-term predictability include the model parameters, prediction errors and the derivates of the used basis functions. To enlarge the maximum attempting time, we present that more suitable basis functions should be those with smaller derivative functions and a fast attenuation where out of the time series range. We compare the long-term predictability of a non-polynomial based algorithm and a polynomial one to prove the success of our method.

• （社）電子情報通信学会の論文
• 2010-04-01

著者

• BU Yun

  School of Communication and Information Engineering, University of Electronic Science and Technology

• WEN Guang-jun

  School of Communication and Information Engineering, University of Electronic Science and Technology

• JIN Hai-Yan

  School of Communication and Information Engineering, University of Electronic Science and Technology

• ZHANG Qiang

  School of Sciences, Southwest Petroleum University

• Zhang Qiang

  School Of Sciences Southwest Petroleum University

• Zhang Qiang

  School Of Pharmaceutical Sciences And State Key Laboratory Of Natural And Biomimetic Drugs Peking Un

• Jin Hai-yan

  School Of Communication And Information Engineering University Of Electronic Science And Technology

• Wen Guang-jun

  School Of Communication And Information Engineering University Of Electronic Science And Technology

• Bu Yun

  School Of Communication And Information Engineering University Of Electronic Science And Technology

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