Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 21, Issue 1, Pages 63-72Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2007.03.002
Keywords
storm surge; typhoon; surge deviation; short term; back-propagation neural network
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It is essential to forecast the variation of storm surge in coastal areas during the typhoon attacks. Conventional investigations of storm surge often used the method of numerical hydrodynamic models or empirical formula. In this paper, the back-propagation neural network (BPN) is applied to predict the short-term typhoon surge and surge deviation in order to overcome the problem of exclusive and nonlinear relationships. The observations obtained during three typhoons of Taichung harbor in Taiwan are verified by the present model. From the comparison with numerical methods, it can be found that the short-term storm surge and surge deviation can be efficiently predicted 1 to 6 h ahead using BPN. (c) 2007 Elsevier Ltd. All rights reserved.
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