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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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NHESS | Articles | Volume 19, issue 3
Nat. Hazards Earth Syst. Sci., 19, 629–653, 2019
https://doi.org/10.5194/nhess-19-629-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Advances in computational modelling of natural hazards and...

Nat. Hazards Earth Syst. Sci., 19, 629–653, 2019
https://doi.org/10.5194/nhess-19-629-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Mar 2019

Research article | 25 Mar 2019

Application of the Levenburg–Marquardt back propagation neural network approach for landslide risk assessments

Junnan Xiong et al.
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (24 Feb 2019) by Albert J. Kettner
AR by Anna Wenzel on behalf of the Authors (27 Feb 2019)  Author's response    Manuscript
ED: Publish as is (27 Feb 2019) by Albert J. Kettner
Publications Copernicus
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Short summary
We want to know which areas are prone to landslides and where pipelines are more unsafe. Through a model, we determined that 33.18 % and 40.46 % of the slopes in the study are were in high-hazard and extremely high-hazard areas, respectively. The number and length of pipe segments in the highly vulnerable and extremely vulnerable areas accounted for about 12 % of the total. In general, the pipeline risk within Qingchuan and Jian'ge counties was relatively high.
We want to know which areas are prone to landslides and where pipelines are more unsafe. Through...
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