Research on landslide susceptibility prediction model based on LSTM-RF-MDBN

Author:

Yang Xiaoyi,Fan XinyueORCID,Wang Kai,Zhou Zhongli

Funder

Sichuan Science and Technology Program

Opening Fund of Sichuan Mineral Resources Research Center

General Program of Sichuan Center for Disaster Economy Research

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Reference36 articles.

1. Cao W, Fu Y, Dong Q, Wang H, Ren Y, Li Z, Du Y (2023) Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning. China Geology 6(03):409–419

2. Chen W, Li W (2014) Application of weights-of-evidence model in landslide susceptibility mapping at Baozhong region in Baoji, China. Electron J Geotech Eng 19:791–810

3. Dadashova B, Arenas-Ramires B, Mira-Mcwillaims J, Dixon K, Lord D (2020) Analysis of crash injury severity on two trans-European transport network corridors in Spain using discrete-choice models and random forests. Traffic Inj Prev 21(3):228–233

4. Dahlquist MP, West AJ (2019) Initiation and runout of post-seismic debris flows: insights from the 2015 Gorkha earthquake. Geophys Res Lett 46(16):9658–9668

5. Das P, Patwa D, G V, Bharat TV (2022) Influencing factors on the simulation of rainfall-induced landslide prediction based on case study. Bull Eng Geol Environ 81(5):1–13

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