Exploring deep learning models for roadside landslide prediction: Insights and implications from comparative analysis-Reference-Cited by-同舟云学术

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Exploring deep learning models for roadside landslide prediction: Insights and implications from comparative analysis

Published:2024-09 Issue: Volume: Page:103741
ISSN:1474-7065
Container-title:Physics and Chemistry of the Earth, Parts A/B/C
language:en
Short-container-title:Physics and Chemistry of the Earth, Parts A/B/C

Author:

Viet Tiep Nguyen,Duc Dam Nguyen,Duc Manh Nguyen,Trong Cong Cao,Hung Mai Sy,Van Le Hiep,Prakash Indra,Phạm Binh Thai

Publisher

Elsevier BV

Reference83 articles.

1. Novel ensemble forecasting of streamflow using locally weighted learning algorithm;Adnan;Sustainability,2021

2. Evaluating the influence of road construction on landslide susceptibility in Saudi Arabia’s mountainous terrain: a Bayesian-optimised deep learning approach with attention mechanism and sensitivity analysis;Alqadhi;Environmental Science and Pollution Research,2024

3. Impact of Vegetation Differences on Shallow Landslides: A Case Study in Aso, Japan;Asada;Water,2023

4. Deep learning-based landslide susceptibility mapping;Azarafza;Scientific reports,2021

5. Group-occurring landslides and debris flows caused by the continuous heavy rainfall in June 2019 in Mibei Village, Longchuan County, Guangdong Province, China;Bai;Natural Hazards,2021

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