| This paper mainly reports on the training/generalization of experimental data on a scour-curve、 which is a two dimensional locus remained when ice keel ploughs the seabed、 by a Neural-Network (NN). As a result of training、 the multiple correlation between estimated value by NN after training and experimental values was more than 0.99. We proposed that this method could replace a nonlinear multiple-regression analysis、 which is very difficult to be applied when unknown parameters are independent. The NN model driven by an extensive data set will be useful tool for developing a practical method for estimation of scour depth by combining it with a mechanical ice scour model that we had already developed. |
