Application of Artificial Neural Network in the typhoon flood prediction system - A case study in Shanghai, China

Xiaodong Li, Zhongyang Guo, Ran Xu, Xiaoyan Dai, Yizhi Hu, Shufeng Ye

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

In order to decrease the damages caused by typhoon, an Artificial Neural Network (ANN) model has been established to predict the trend of storm flood in Shanghai, China. The model has capacity to simulate the brain's thinking process objectively and avoid the influence of the forecasters' subjective judgment. The present model is capable to predict the 12-hour ahead typhoon surge deviation in high tide efficiently. At the same time, an intelligent storm-flood forecasting system is designed and built, and the system not only can predict the storm flood in the future 12 hours, but also is useful to mitigate the typhoon disasters in Shanghai. It has been proved that the ANN model is a new effective way to predict the storm surge, and the intelligent storm-flood forecasting system is a kind of new method to manage the typhoon disasters as well.

Original languageEnglish
Title of host publicationProceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Pages191-195
Number of pages5
DOIs
StatePublished - 2010
Event2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010 - Sanya, China
Duration: 23 Oct 201024 Oct 2010

Publication series

NameProceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Volume1

Conference

Conference2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Country/TerritoryChina
CitySanya
Period23/10/1024/10/10

Keywords

  • ANN
  • BP
  • Prediction
  • Storm flood

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