ANN-based response surface method and its application to ultimate strength of plates

被引：0
|
作者：
Pu, YC [1 ]
Mesbahi, E [1 ]
ElHewy, AH [1 ]
机构：
[1] Newcastle Univ, Sch Marine Sci & Technol, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
来源：
PROCEEDINGS OF THE FIFTEENTH (2005) INTERNATIONAL OFFSHORE AND POLAR ENGINEERING CONFERENCE, VOL 4 | 2005年
关键词：
ANN-based response surface method; artificial neural networks; response surface method; ultimate strength of plates; design equations of plates;
D O I：
暂无
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：
In this paper, artificial neural networks (ANN)-based response surface method (RSM) is presented. This method is compared with conventional polynomial-based RSM in the context of structural reliability analysis. ANN-based RSM is then applied to predict ultimate strength of unstiffened plates. It is found out that the ANN-based RSM is more accurate and efficient than polynomial-based RSM in structural reliability analysis. ANN-based RSM can more accurately predict ultimate strength of unstiffened plates than the existing empirical formulae.
引用
收藏
页码：752 / 758
页数：7
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