Depth prediction of urban waterlogging based on BiTCN-GRU modeling.
With China's rapid urbanization and the increasing frequency of extreme weather events, heavy rainfall-induced urban waterlogging has become a persistent and pressing challenge. Accurately predicting waterlogging depth is essential for disaster prevention and loss mitigation. However, existing...
Saved in:
| Main Authors: | Quan Wang, Mingjie Tang, Pei Shi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0321637 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model
by: Yi Zhang, et al.
Published: (2025-02-01) -
Fault Diagnosis of Rolling Element Bearing Based on BiTCN-Attention and OCSSA Mechanism
by: Yuchen Yang, et al.
Published: (2025-04-01) -
Research on Fault Prediction of Power Devices in Rod Control Power Cabinets Based on BiTCN-Attention Transfer Learning Model
by: Zhi Chen, et al.
Published: (2024-10-01) -
Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm
by: Pei Shi, et al.
Published: (2025-08-01) -
Research on Predictive Analysis Method of Building Energy Consumption Based on TCN-BiGru-Attention
by: Sijia Fu, et al.
Published: (2024-10-01)