Back-propagation neural network for the prediction of the short-term storm surge in Taichung harbor, Taiwan

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.