Application of artificial intelligence method in urban flooding warning and forecast

Sheng Hsueh Yang*, D. L. Chang, H. J. Wang, S. L. Hsieh, Keh-Chia Yeh, S. J. Wu, C. T. Hsu, C. H. Chang, L. W. Leu, J. H. Kao, M. C. Chen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Heavy rain is one of the main reasons for urban flooding. In the face of the floods, the application the artificial intelligence (AI) can provide timely flood forecasting, and combined with space display, providing spatial information on possible flooding disasters, allowing flooding disaster management units to have more early warning time to respond and provide. This paper uses the spatial rainfall uncertainty analysis and the hydrological, hydraulic and urban inundation model simulation results in urban areas to build big data databases, such as 1000 sets of different spatial rainfall and urban flooding simulation results. Through the AI data classification, the rainfall threshold value setting and feature parameter train. After the completion, the real-time and forecast rainfall data can use to forecast the rainfall and real-time display of the urban flooding. Finally, the real-time CCTV image data and the flooding analysis result can use to provide the urban flooded image and the flooding depth. And strive for effective disaster prevention response time.

Original languageEnglish
JournalProceedings of the International Conference on Natural Hazards and Infrastructure
StatePublished - Jun 2019
Event2nd International Conference on Natural Hazards and Infrastructure, ICONHIC 2019 - Chania, Greece
Duration: 23 Jun 201926 Jun 2019

Keywords

  • Artificial intelligence
  • Flood forecasting
  • Real-time display
  • Urban flooding

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