Open Access

ABSTRACT

Probabilistic Neural Network for Predicting the Stability numbers of Breakwater Armor Blocks

by Doo Kie Kim¹, Dong Hyawn Kim², Seong Kyu Chang¹, Sang Kil Chang¹

1 Department of Civil and Environmental Engineering, Kunsan National University, Miryong, Kunsan, Jeonbuk, Korea
2 Department of Ocean System Engineering, Kunsan National University, Miryong, Kunsan, Jeonbuk, Korea

The International Conference on Computational & Experimental Engineering and Sciences 2007, 2(2), 35-40. https://doi.org/10.3970/icces.2007.002.035

Abstract

The stability numbers determining the Armor units are very important to design breakwaters, because armor units are designed for defending breakwaters from repeated wave loads. This study presents a probabilistic neural network (PNN) for predicting the stability number of armor blocks of breakwaters. PNN used the experimental data of van der Meer as train and test data. The estimated results of PNN were compared with those of empirical formula and previous artificial neural network (ANN) model. The comparison results showed the efficiency of the proposed method in the prediction of the stability numbers in spite of data incompleteness and incoherence. The proposed method was proved to an effective tool for designers of rubble mound breakwaters to support their decision process and to improve design efficiency.

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