A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network
https://orcid.org/0000-0002-5036-6313
https://orcid.org/0009-0002-3712-3728
https://orcid.org/0000-0002-7616-2685
A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network
https://orcid.org/0000-0002-5036-6313
https://orcid.org/0009-0002-3712-3728
https://orcid.org/0000-0002-7616-2685
A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network
https://orcid.org/0000-0002-5036-6313
https://orcid.org/0009-0002-3712-3728
https://orcid.org/0000-0002-7616-2685
A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network
Journal of Rock Mechanics and Geotechnical Engineering
Cui, Hongzhi (author) / Tong, Bin (author) / Wang, Tao (author) / Dou, Jie (author) / Ji, Jian (author)
2024-09-01
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2013
| Taylor & Francis Verlag | 2022
A novel physically-based model for updating landslide susceptibility
| British Library Online Contents | 2019