Application and prospects of machine learning for rockfalls, landslides and debris flows
Rockfalls, landslides, and debris flows present significant threats to the safety of mountainous communities globally. With the rapid development of computer technology and the onset of the “big data” era, new avenues and momentum have emerged in disaster prevention and mitigation. Artificial intell...
Saved in:
| Main Authors: | Jiazhu WANG, Yongbo TIE, Yongjian BAI, Yanchao GAO, Donghui WANG, Mingzhi ZHANG |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Hydrogeology & Engineering Geology
2025-07-01
|
| Series: | Shuiwen dizhi gongcheng dizhi |
| Subjects: | |
| Online Access: | https://www.swdzgcdz.com/en/article/doi/10.16030/j.cnki.issn.1000-3665.202402011 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
RECENT ADVANCES IN SIMULATING LANDSLIDE AND DEBRIS FLOW
by: Wei Wu
Published: (2021-01-01) -
Quantitative evaluation of influencing factors for landslide, rockfall and debris flow hazards in the Nyingchi area of Xizang Autonomous Region
by: Mingwei YU, et al.
Published: (2024-12-01) -
Quantitative Rockfall Hazard Assessment of the Norwegian Road Network and Residences at an Indicative Level from Simulated Trajectories
by: François Noël, et al.
Published: (2025-02-01) -
Landslide risk on photovoltaic power stations under climate change
by: Chae Yeon Park, et al.
Published: (2024-12-01) -
Conic-Based 3D Rockfall Modeling with QGIS-Qproto Software: A Case Study of Mazı Village, Nevşehir (Ürgüp)
by: Mustafa Utlu, et al.
Published: (2023-07-01)