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

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Final revised paper (published on 07 Dec 2017)
Preprint (discussion started on 29 Mar 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

SC1: 'Review for the manuscript', Yourong Liu, 22 May 2017
- AC2: 'Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China', HUIMING TNAG, 10 Jul 2017
  - SC2: 'Short comment', Yourong Liu, 19 Jul 2017
RC1: 'Review: Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China', Anonymous Referee #1, 01 Jun 2017
- AC1: 'Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China', HUIMING TNAG, 10 Jul 2017
  - RC2: 'Review of : Landslide displacement prediction using GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China', Anonymous Referee #1, 21 Jul 2017
RC3: 'Interactive comment on: Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China', Anonymous Referee #2, 28 Sep 2017
- AC3: 'Response to Reviewer’s Comments', HUIMING TNAG, 13 Oct 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (23 Oct 2017) by Thomas Glade

AR by HUIMING TNAG on behalf of the Authors (28 Oct 2017) Author's response Manuscript

ED: Publish as is (02 Nov 2017) by Thomas Glade

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.