Data‐driven flood emulation: Speeding up urban flood predictions by deep convolutional neural networks
Abstract Computational complexity has been the bottleneck for applying physically based simulations in large urban areas with high spatial resolution for efficient and systematic flooding analyses and risk assessment. To overcome the issue of long computational time and accelerate the prediction pro...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-03-01
|
| Series: | Journal of Flood Risk Management |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/jfr3.12684 |