Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
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 (Autor:in) / Tong, Bin (Autor:in) / Wang, Tao (Autor:in) / Dou, Jie (Autor:in) / Ji, Jian (Autor:in)
01.09.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| British Library Online Contents | 2013
| Taylor & Francis Verlag | 2022