Articles | Volume 21, issue 4
https://doi.org/10.5194/nhess-21-1179-2021
https://doi.org/10.5194/nhess-21-1179-2021
Research article
 | 
06 Apr 2021
Research article |  | 06 Apr 2021

Online urban-waterlogging monitoring based on a recurrent neural network for classification of microblogging text

Hui Liu, Ya Hao, Wenhao Zhang, Hanyue Zhang, Fei Gao, and Jinping Tong

Viewed

Total article views: 2,479 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,825 583 71 2,479 135 58 58
  • HTML: 1,825
  • PDF: 583
  • XML: 71
  • Total: 2,479
  • Supplement: 135
  • BibTeX: 58
  • EndNote: 58
Views and downloads (calculated since 16 Nov 2020)
Cumulative views and downloads (calculated since 16 Nov 2020)

Viewed (geographical distribution)

Total article views: 2,479 (including HTML, PDF, and XML) Thereof 2,343 with geography defined and 136 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
We trained a recurrent neural network model to classify microblogging posts related to urban waterlogging and establish an online monitoring system of urban waterlogging caused by flood disasters. We manually curated more than 4400 waterlogging posts to train the RNN model so that it can precisely identify waterlogging-related posts of Sina Weibo to timely determine urban waterlogging.
Altmetrics
Final-revised paper
Preprint