| 混沌时间序列单变量和多变量重构的预测比较 |
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| 引用本文： | 王海燕,朱梅.混沌时间序列单变量和多变量重构的预测比较[J].东南大学学报,2003,19(4):414-417. |
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| 作者姓名： | 王海燕 朱梅 |
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| 作者单位： | [1]东南大学经济管理学院，南京210096 [2]东南大学数学系，南京210096 |
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| 摘 要： | 提出了多变量混沌时间序列相空间延迟重构中延迟时间间隔和嵌入维数的选取方法，给出了多变量混沌时间序列的局部平均预测法，局部线性预测法和BP神经网络预测法等3种非线性预测方法．通过Lorenz系统的仿真计算表明，无论用3种非线性预测方法中的哪一种，多变量混沌时间序列要比单变量混沌时间序列的预测误差小得多，即使前的数据长度只有后的一半，前的预测误差也要小很多．另外从预测误差最小的角度验证了多变量混沌时间序列相空间延迟重构中延迟时间间隔和嵌入维数选取方法的有效性．
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| 关 键 词： | 混沌时间序列 局部平均预测法 局部线性预测法 BP神经网络预测法 复杂系统 |
A prediction comparison between univariate and multivariate chaotic time series |
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| Wang Haiyan,Zhu Mei.A prediction comparison between univariate and multivariate chaotic time series[J].Journal of Southeast University(English Edition),2003,19(4):414-417. |
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| Authors: | Wang Haiyan Zhu Mei |
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| Abstract: | The methods to determine time delays and embedding dimensions in the phase space delay reconstruction of multivariate chaotic time series are proposed. Three nonlinear prediction methods of multivariate chaotic time series including local mean prediction, local linear prediction and BP neural networks prediction are considered. The simulation results obtained by the Lorenz system show that no matter what nonlinear prediction method is used, the prediction error of multivariate chaotic time series is much smaller than the prediction error of univariate time series, even if half of the data of univariate time series are used in multivariate time series. The results also verify that methods to determine the time delays and the embedding dimensions are correct from the view of minimizing the prediction error. |
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| Keywords: | multivariate chaotic time series phase space reconstruction prediction neural networks |
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