Application of probabilistic neural network to design breakwater armor blocks

被引：24

作者：

Kim, Dookie ^{[2
]}

Kim, Dong Hyawn ^{[1
]}

Chang, Seongkyu ^{[2
]}

机构：

[1] Kunsan Natl Univ, Dept Ocean Syst Engn, Kunsan 573701, Jeonbuk, South Korea

[2] Kunsan Natl Univ, Dept Civil & Environm Engn, Kunsan, Jeonbuk, South Korea

来源：

OCEAN ENGINEERING | 2008年 / 35卷 / 3-4期

关键词：

breakwater; armor block; stability number; probabilistic neural network; probability density function;

D O I：

10.1016/j.oceaneng.2007.11.003

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

This study presents a probabilistic neural network (PNN) technique for predicting the stability number of armor blocks of breakwaters. The PNN is prepared using the experimental data of Van der Meer. The predicted stability numbers of the PNN are compared with those of previous studies, i.e. by an empirical formula and a previous neural network model. The agreement index between the measured and predicted stability numbers by PNN are better than those by the previous studies. The PNN offers a way to interpret the network's structure in the form of a probability density function and it is easy to implement. Therefore, it can be an effective tool for designers of rubble mound breakwaters. (c) 2007 Elsevier Ltd. All rights reserved.

引用

页码：294 / 300

页数：7

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