An advanced probabilistic neural network for the design of breakwater armor blocks

Abstract

In this study, an advanced probabilistic neural network (APNN) method is proposed to reflect the global probability density function (PDF) by summing up the heterogeneous local PDF which is automatically determined in the individual standard deviation of variables. The APNN is applied to predict the stability number of armor blocks of breakwaters using the experimental data of van den Meer, and the estimated results of the APNN are compared with those of an empirical formula and a previous artificial neural network (ANN) model. The APNN shows better results in predicting the stability number of armor blocks of breakwater and it provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.