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Storm surge disaster evaluation model based on an artificial neural network

Chinese Journal of Oceanology and Limnology : Volume 29, Issue 4, July 2011

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Storm surge disaster evaluation model based on an artificial neural network

Content Provider	Springer Nature Link
Author	Ji, Fang Hou, Yijun
Copyright Year	2011
Abstract	Back propagation is employed to forecast the current of a storm with various characteristics of storm surge; the technique is thus important in disaster forecasting. One of the most fuzzy types of information in the prediction of geological calamity is handled employing the information diffusion method. First, a single-step prediction model and neural network prediction model are employed to collect influential information used to predict the extreme tide level. Second, information is obtained using the information diffusion method, which improves the precision of risk recognition when there is insufficient information. Experiments demonstrate that the method proposed in this paper is simple and effective and provides better forecast results than other methods. Future work will focus on a more precise forecast model.
Starting Page	1142
Ending Page	1146
Page Count	5
File Format	PDF
ISSN	02544059
Journal	Chinese Journal of Oceanology and Limnology
Volume Number	29
Issue Number	5
e-ISSN	19935005
Language	English
Publisher	SP Science Press
Publisher Date	2011-08-08
Publisher Place	Heidelberg
Access Restriction	Subscribed
Subject Keyword	storm surge information diffusion neural network prediction model extreme tide level risk Oceanography
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology Oceanography

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