Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China

Wen, Tao; Tang, Huiming; Wang, Yankun; Lin, Chengyuan; Xiong, Chengren

doi:https://doi.org/10.5194/nhess-17-2181-2017

Articles | Volume 17, issue 12

https://doi.org/10.5194/nhess-17-2181-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-17-2181-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 12

Research article

|

07 Dec 2017

Research article |

| 07 Dec 2017

Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China

Tao Wen, Huiming Tang, Yankun Wang, Chengyuan Lin, and Chengren Xiong

Data sets

Shuping landslide-Rainfall and Reservoir water level T. Wen, H. Tang, Y. Wang, C. Lin, and C.Xiong https://doi.org/10.13140/RG.2.2.27329.04964

Short summary

Landslide displacement prediction is one of the focuses of landslide research. In this paper, time series analysis was used to decompose the cumulative displacement of landslide into a trend component and a periodic component. Then LSSVM model and GA were used to predict landslide displacement. The results show that the GA-LSSVM model can be effectively used to predict landslide displacement and reflect the corresponding relationships between the major influencing factors and the displacement.