Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Displacement prediction of step-like landslides based on feature optimization and VMD-Bi-LSTM: a case study of the Bazimen and Baishuihe landslides in the Three Gorges, China
Abstract Displacement prediction is critical for the early detection of landslides, and the empirical, statistical, and machine learning models have been commonly used. In the Three Gorges reservoir area (TGRA), many landslides experience step-like deformations due to the periodic change of influencing factors. In this study, a novel and dynamic model is proposed to predict the displacements of step-like landslides. Two typical landslides in the TGRA are taken as case studies. Variational mode decomposition (VMD) is used to decompose the cumulative displacements into stochastic, periodic, and trend components. The influencing factors are decomposed into low-frequency and high-frequency components. Two principles, including the physical connotation and minimum sample entropy, are employed to optimize the VMD parameters. The trend displacement is fitted and predicted by a polynomial expression with an optimized order, and the periodic and stochastic displacements are dynamically modeled by the bidirectional long short-term memory (LSTM) model. The cumulative displacement prediction is the addition of the three displacement components. The proposed model has been shown to exhibit superior performance in the displacement prediction of step-like landslides. To achieve acceptable prediction, a size ratio between the training and testing datasets greater than or equal to five is recommended. The min–max and zero-mean normalizations are applicable to the data preprocessing of this work.
Displacement prediction of step-like landslides based on feature optimization and VMD-Bi-LSTM: a case study of the Bazimen and Baishuihe landslides in the Three Gorges, China
Abstract Displacement prediction is critical for the early detection of landslides, and the empirical, statistical, and machine learning models have been commonly used. In the Three Gorges reservoir area (TGRA), many landslides experience step-like deformations due to the periodic change of influencing factors. In this study, a novel and dynamic model is proposed to predict the displacements of step-like landslides. Two typical landslides in the TGRA are taken as case studies. Variational mode decomposition (VMD) is used to decompose the cumulative displacements into stochastic, periodic, and trend components. The influencing factors are decomposed into low-frequency and high-frequency components. Two principles, including the physical connotation and minimum sample entropy, are employed to optimize the VMD parameters. The trend displacement is fitted and predicted by a polynomial expression with an optimized order, and the periodic and stochastic displacements are dynamically modeled by the bidirectional long short-term memory (LSTM) model. The cumulative displacement prediction is the addition of the three displacement components. The proposed model has been shown to exhibit superior performance in the displacement prediction of step-like landslides. To achieve acceptable prediction, a size ratio between the training and testing datasets greater than or equal to five is recommended. The min–max and zero-mean normalizations are applicable to the data preprocessing of this work.
Displacement prediction of step-like landslides based on feature optimization and VMD-Bi-LSTM: a case study of the Bazimen and Baishuihe landslides in the Three Gorges, China
Zhang, Ke (Autor:in) / Zhang, Kai (Autor:in) / Cai, Chenxi (Autor:in) / Liu, Wenlian (Autor:in) / Xie, Jianbin (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
56.00$jBauwesen: Allgemeines
/
38.58
Geomechanik
/
38.58$jGeomechanik
/
56.20
Ingenieurgeologie, Bodenmechanik
/
56.00
Bauwesen: Allgemeines
/
56.20$jIngenieurgeologie$jBodenmechanik
RVK:
ELIB18
Displacement prediction in colluvial landslides, Three Gorges Reservoir, China
| British Library Online Contents | 2013
Quantitative risk analysis for landslides: the case of the Three Gorges area, China
| British Library Online Contents | 2015
Landslides in the Wushan-Zigui region of the Three Gorges, China
| Online Contents | 2007
Entropy-Based Hazard Degree Assessment for Typical Landslides in the Three Gorges Area, China
| Springer Verlag | 2009