Landslide Displacement Prediction Based on a Combined VMD-Kalman-GM Model
In order to improve the prediction effect of rainfall on landslide displacements,the article establishes a combined prediction method of variational modal decomposition ( VMD) algorithm and improved Kalman filter ( Kalman) and improved grey model ( GM) . The ar-ticle decomposes the landslide surface monitoring displacement series into different frequency components based on the variational modal de-composition algorithm,and obtains the fluctuation and trend values after the time series combination. The VMD-Kalman-GM combined pre-diction model was established by combining the dynamic prediction of the landslide displacement with the dynamic grey prediction model to predict the trend value,and finally synthesizing the fluctuation value and the trend value to obtain the landslide prediction value. The predic-tion results were compared with the actual measured values using the monitoring data of the Bazimen landslide in the Three Gorges reservoir area of China as an example,verifying the feasibility and accuracy of the method and providing a new method for the prediction of landslide displacements.
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