引用本文: 范千, 花向红. 基于相空间重构与支持向量机预测滑坡位移的一种新方法[J]. 武汉大学学报 ( 信息科学版), 2009, 34(2): 248-251.
FAN Qian, HUA Xianghong. A Novel Method for Forecasting Landslide Displacement Based on Phase Space Reconstruction and Support Vector Machine[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 248-251.
 Citation: FAN Qian, HUA Xianghong. A Novel Method for Forecasting Landslide Displacement Based on Phase Space Reconstruction and Support Vector Machine[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 248-251.

A Novel Method for Forecasting Landslide Displacement Based on Phase Space Reconstruction and Support Vector Machine

• 摘要: 提出了一种基于相空间重构与支持向量机预测滑坡位移的新方法。首先,以滑坡位移时间序列的混沌特性为基础,对其应用互信息法计算最优时间延迟;然后,利用小波变换对滑坡位移序列数据进行频域分解,应用Cao氏方法对分解后的每个分量序列分别计算其最佳嵌入维数,在此基础上,对各个分量序列进行相空间重构,利用支持向量机对每个分量单独进行建模预测;最后,将各分量预测结果进行小波重构,得到最终预测结果。实例证明,该方法可以在滑坡位移预测中获得有效的应用。

Abstract: We presented a novel method for forecasting landslide displacement based on phase space reconstruction and support vector machine.Firstly,based on the chaotic characteristics of landslide displacement time series,mutual information was used to compute the optimal time lag.Then,landslide displacement time series was decomposed into different frequency components through a wavelet transform.We adopted of Cao to compute the optimal embedding dimension of the decomposed series of each component.On the basis of this,phase space reconstruction is performed for each component.Different support vector machines were established to forecast each component.Finally,the predicted results of the components were reconstructed as the final prediction result by wavelet theory.The experimental result show that this method can effectively apply to landslide displacement prediction.

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