Capability Enhancement of Probabilistic Neural Network for the Design of Breakwater Armor Blocks

In this study, the capability of probabilistic neural network (PNN) is enhanced. The proposed PNN is capable of reflecting the global probability density function (PDF) by summing the heterogeneous local PDF automatically determined in the individual standard deviation of variables. The present PNN is applied to predict the stability number of armor blocks of breakwaters using the experimental data of van der Meer, and the estimated results of PNN are compared with those of empirical formula and previous artificial neural network (ANN) model. The PNN showed better results in predicting the stability number of armor blocks of breakwaters and provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.