Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 19, issue 3
Articles | Volume 19, issue 3
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:
https://doi.org/10.5194/nhess-19-629-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 3
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, Ming Sun, Hao Zhang, Weiming Cheng, Yinghui Yang, Mingyuan Sun, Yifan Cao, and Jiyan Wang

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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.
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