Based on the chaotic theory of reconstructing phase space, an improved local average nonlinear noise reduction method is presented.
基于混沌序列重构相空间理论,提出一种改进的局部平均非线性去噪方法。
This paper studies the chaotic time series of the slope displacement forecast. Using the theory of reconstructing phase space in the chaotic time series.
研究边坡位移混沌时间序列的预测,利用混沌系统的相空间重构理论,提出基于小波神经网络的边坡位移预测方法。
The structure of the network is defined by integrating the theory of reconstructing phase space, which makes the efficient prediction information be contained in the network.
结合相空间重构理论确定网络结构,使网络能够包含有效的预测信息。
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