Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model

Zhongyang Guo; Xiaoyan Dai; Xiaodong Li; Shufeng Ye

doi:10.1007/s00343-013-2048-8

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Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model

OriginalPaper | Updated：2023-05-16

- Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model
- Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model
- 海洋湖沼学报（英文） 2013年31卷第1期页码：219-226
- Affiliations：
  
  1. Department of Geography Key Laboratory of Geographic Information Science Ministry of Education East China Normal University
  2. Key Laboratory of Wave Scattering and Remote Sensing Information Fudan University
  3. Key Laboratory of Marine Integrated Monitoring and Applied Technologies of Harmful Algal Blooms State Oceanic Administration
  4. East China Sea Center of Standard and Metrology State Oceanic Administration
- Author bio：
- Funds：
  
  Supported by National Marine Public Scientific Research Fund of China (No. 200905010), the Talent Training Fund Project for Basic Sciences of the National Natural Science Foundation of China (No. J0730534), the Fundamental Research Funds for the Central Universities, the Open Research Funding Program of KLGIS (No. KLGIS2011A12), and the Open Fund from Key Laboratory of Marine Management Technique of State Oceanic Administration (No. 201112)
- DOI：10.1007/s00343-013-2048-8
  中图分类号：
- 网络首发：2013-01-16，
  
  纸质出版：2013
- Accepted：
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Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model[J]. 海洋湖沼学报（英文）, 2013,31(1):219-226.

Guo, Z., Dai, X., Li, X. et al. Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model., Chin. J. Ocean. Limnol. 31, 219–226 (2013). https://doi.org/10.1007/s00343-013-2048-8
Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model[J]. 海洋湖沼学报（英文）, 2013,31(1):219-226. DOI： 10.1007/s00343-013-2048-8.

Guo, Z., Dai, X., Li, X. et al. Predict typhoon-induced storm surge deviation in a principal component back-propagation neural network model., Chin. J. Ocean. Limnol. 31, 219–226 (2013). https://doi.org/10.1007/s00343-013-2048-8 DOI：

摘要

Abstract

To reduce typhoon-caused damages

numerical and empirical methods are often used to forecast typhoon storm surge. However

typhoon surge is a complex nonlinear process that is difficult to forecast accurately. We applied a principal component back-propagation neural network (PCBPNN) to predict the deviation in typhoon storm surge

in which data of the typhoon

upstream flood

and historical case studies were involved. With principal component analysis

15 input factors were reduced to five principal components

and the application of the model was improved. Observation data from Huangpu Park in Shanghai

China were used to test the feasibility of the model. The results indicate that the model is capable of predicting a 12-hour warning before a typhoon surge.

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Keywords

references

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