globalchange  > 气候变化与战略
DOI: 10.1007/s11069-020-04337-6
论文题名:
A novel displacement prediction method using gated recurrent unit model with time series analysis in the Erdaohe landslide
作者: Zhang Y.-G.; Tang J.; He Z.-Y.; Tan J.; Li C.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 105, 期:1
起始页码: 783
结束页码: 813
语种: 英语
中文关键词: Displacement prediction ; Gated recurrent unit model ; Global positioning system (GPS) technology ; Moving average method ; Step-wise landslide
英文关键词: displacement ; early warning system ; GPS ; landslide ; machine learning ; mapping method ; prediction ; time series analysis ; China ; Three Gorges Reservoir
英文摘要: Landslides are natural phenomena, causing serious fatalities and negative impacts on socioeconomic. The Three Gorges Reservoir (TGR) area of China is characterized by more prone to landslides for the rainfall and variation of reservoir level. Prediction of landslide displacement is favorable for the establishment of early geohazard warning system. Conventional machine learning methods as forecasting models often suffer gradient disappearance and explosion, or training is slow. Hence, a dynamic method for displacement prediction of the step-wise landslide is provided, which is based on gated recurrent unit (GRU) model with time series analysis. The establishment process of this method is interpreted and applied to Erdaohe landslide induced by multi-factors in TGR area: the accumulative displacements of landslide are obtained by the global positioning system; the measured accumulative displacements is decomposed into the trend and periodic displacements by moving average method; the predictive trend displacement is fitted by a cubic polynomial; and the periodic displacement is obtained by the GRU model training. And the support vector machine (SVM) model and GRU model are used as comparisons. It is verified that the proposed method can quite accurately predict the displacement of the landslide, which benefits for effective early geological hazards warning system. Moreover, the proposed method has higher prediction accuracy than the SVM model. © 2020, Springer Nature B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169518
Appears in Collections:气候变化与战略

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作者单位: Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China; School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, 221000, China; China Geological Survey, Beijing, 100037, China; Xiamen Xijiao Hard Science Industrial Technology Research Institute Co., Ltd, Xiamen, 316000, China; College of Civil Engineering, Huaqiao University, Xiamen, 316000, China; School of Civil Engineering, Central South University, Changsha, 410083, China; School of Mechanical Engineering, Tianjin University, Tianjin, 300072, China

Recommended Citation:
Zhang Y.-G.,Tang J.,He Z.-Y.,et al. A novel displacement prediction method using gated recurrent unit model with time series analysis in the Erdaohe landslide[J]. Natural Hazards,2021-01-01,105(1)
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