Modified Probabilistic Neural Network Considering heterogeneous Probabilisticc Density Functions in the Design of Break Water  

Oleh:

Doo Kie Kim ; Dong Hyawn Kim ; Seong, Kyu Chang ; Sang, Kil Chang

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: KSCE Journal of Civil Engineering vol. 11 no. 2 (2007), page 65-71.
Topik: Armor Block; Stability Number Mullivariate Gaussian Distribution; Classification; Modified Probabilistic Neural Network (MPNN)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: KK25.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this study, a modified probabilistic neural network approach is proposed. The global probability density function (PDF) of variables is reflected by summing the heterogeneous local PDFs automatically determined in the individual standard deviation of each variable. The proposed modified probabilistic neural network (MPNN) 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 the MPNN are compared with those of conventional probabilistic neural network. The MPNN shows improved results in predicting the stability number of armor blocks of breakwaters and in providing the promising reliability for stability numbers estimated by using the individual standard deviation in a variable.

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