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中国物理学会期刊

混沌时间序列多步自适应预测方法

CSTR: 32037.14.aps.55.1666

A novel multi-step adaptive prediction method for chaotic time series

CSTR: 32037.14.aps.55.1666
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  • 针对混沌时间序列局域自适应预测方法在多步预测中预测器系数无法调节的问题,根据混沌时间序列的短期可预测性及自适应算法的自适应跟踪混沌运动轨迹的特点,提出了混沌时间序列多步自适应预测方法.仿真结果表明,此方法的多步预测性能明显好于局域自适应预测方法的多步预测性能.

     

    Based on the short-term predictability of chaotic time series and the adaptive tracking chaotic trajectory of adaptive algorithm, a novel multi-step adaptive prediction method is proposed in this paper to resolve the problem of adjusting the filter parameters of the local adaptive prediction method during multi-step prediction. Simulation results show that this multi-step adaptive prediction method can be successfully used to make multi-step predictions, and its performance is better than that of the local adaptive prediction algorithm.

     

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