An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks

An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks

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...

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Veröffentlicht in:China ocean engineering 2007-12, Vol.21 (4), p.597-610
1. Verfasser: Dookie KIM Dong Hyawn KIM Seongkyu CHANG Gil Lim YOON
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分析方法
防浪堤
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description 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 der Meet, 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 bilks of breakwater and it provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.
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subjects 分析方法
防浪堤
title An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks
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