Estimation of Tsunami Run-up Height by Three Artificial Neural Network Methods

Tsunami run-up height is a significant parameter for dimemsions of coastal structures.In the present study,tsunami run-up heights are estimated by three different Artificial Neural Network (ANN) models,i.e.Feed Forward Back Propagation (FFBP),Radial Basis Functions (RBF) and Generalized Regression Neural Network (GRNN).As the input for the ANN configuration,the wave height (H) values are employed.It is shown that the tsunami run-up height values are closely approximated with all of the applied ANN methods.The ANN estimations are slightly superior to those of the empirical equation.It can he seen that the ANN applications are especially significant in the absence of adequate number of laboratory experiments.The restdts also prove that the available experiment data set can he extended with ANN simulations.This may be helpful to decrease the burden of the experimental studies and to supply results for comparisons.