A spatial–temporal deep learning-based warning system against flooding hazards with an empirical study in Taiwan
Bibliographic Data
| ID | 22028975 |
|---|---|
| Authors | Kuo-Hao Chang (0000-0002-3828-960X, National Science and Technology Center for Disaster Reduction, corresponding author), Yun-Ting Chiu (National Tsing Hua University), Wen-Ray Su (0000-0001-9788-2545, National Science and Technology Center for Disaster Reduction), Yi-Chiang Yu, Yi‐Chiang Yu (National Science and Technology Center for Disaster Reduction), Chih-Hsin Chang (National Science and Technology Center for Disaster Reduction) |
| Year | 2024 |
| Volume | 102 |
| Pages | 104263 |
| Publication date | 2024-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2024.104263 |
| OpenAlex | W4390843663 |
| Language | EN |
| Citations received | 1 |
| References cited | 31 |
Data mining · Deep learning · Early warning system · Flood myth · Flood warning · Geography · Machine learning · Random forest · Telecommunications · Warning system · Computer Science · Environmental Science · Flood Risk Assessment and Management · Hydrological Forecasting Using AI · Hydrology and Watershed Management Studies · Artificial Intelligence
Long Short-Term Memory
Hazard and vulnerability in urban flood risk mapping
A mixed approach for urban flood prediction using Machine Learning and GIS
Evaluating urban flood risk using hybrid method of Topsis and machine learning
An interactive Web-GIS fluvial flood forecast and alert system in operation in Portugal
Explanatory pragmatism
Operational early warning systems for water-related hazards in Europe
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |