论文信息 - EFFECTS OF ZERO-OVERTOPPING DATA IN ARTIFICIAL NEURAL NETWORK PREDICTIONS

EFFECTS OF ZERO-OVERTOPPING DATA IN ARTIFICIAL NEURAL NETWORK PREDICTIONS

This study examined the applicability of artificial neural networks (ANNs) to the estimation of wave overtopping over sloping seawalls, especially with regard to the best structure for an ANN. Correlation coefficients between measurements and predictions were best when 6 input units and 12 hidden layer units were employed. Bayesian Regularization, recommended in this study, does not require a validation data set. It was found that the ANNs could not recognize when wave overtopping failed to occur if data on zero overtopping were omitted.

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