Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions-Reference-Cited by-同舟云学术

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Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions

Published:2024-08 Issue: Volume:179 Page:106130
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Jiang Hu,Zou Qiang,Zhu Yunqiang,Li Yong,Zhou Bin,Zhou Wentao,Yao Shunyu,Dai Xiaoliang,Yao Hongkun,Chen Siyu

Funder

National Natural Science Foundation of China

Sichuan Province Science and Technology Support Program

Science and Technology Department of Sichuan Province

Chinese Academy of Sciences

Institute of Mountain Hazards and Environment Chinese Academy of Sciences

Publisher

Elsevier BV

Reference134 articles.

1. African vultures optimization algorithm: a new nature-inspired metaheuristic algorithm for global optimization problems;Abdollahzadeh;Comput. Ind. Eng.,2021

2. Short-term rainfall forecasting using machine learning-based approaches of PSO-SVR, LSTM and CNN;Adaryani;J. Hydrol.,2022

3. A warning system for rainfall-induced shallow failures;Aleotti;Eng. Geol.,2004

4. Lake outburst and debris flow disaster at Kedarnath, June 2013: hydrometeorological triggering and topographic predisposition;Allen;Landslides,2016

5. Debris flow prediction with machine learning: smart management of urban systems and infrastructures;Bai;Neural Comput. Appl.,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel framework for predicting glacial lake outburst debris flows in the Himalayas amidst climate change;Science of The Total Environment;2024-10

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