Last, the next sample of the original time series was predicted by another neural network.
最新的原始的时间序列的下一个样本由另一个神经网络预测。
Test results show the method can much better reflect the original time series. Comparing this method with the existed ones, the smaller fitting errors are achieved.
实验结果表明,与已有方法相比,该方法能近似表示原时间序列,且拟合后的时间序列和原时间序列之间的拟合误差更小。
Finally, the forecasting results of chaotic models are reconstructed based on the wavelet packet theory and the forecasting result of the original time series can be obtained.
再将混沌模型预测的结果进行小波包重构,则得到原始时序的预测结果。
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