A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.

采用新型多重分支时间延迟神经网络进行混沌时间序列预测研究。

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Finally, connecting embedding theory with prediction errors, we propose a new prediction method to chaotic time series based on embedding technique and prediction errors on tested sets.

最后，结合嵌入理论和预测误差，提出了基于嵌入技术和确定集上预测误差的混沌时序预测方法。

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Based on this, the average predictable size and the longest predictable size of chaotic time series are provided in this paper to definite the time range of short-term prediction.

基于此，给出了混沌时间序列的平均可预测尺度及最长可预测尺度，以此来界定短期预测的时间范围。

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