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

Y.C. Pu, E. Mesbahi, A.H. El Hewy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the Fifteenth (2005) International Offshore and Polar Engineering Conference, Vol 4
PublisherThe International Society Offshore and Polar Engineers
Pages752-758
Publication statusPublished - 2005
Externally publishedYes

Publication series

NameInternational Offshore and Polar Engineering Conference Proceedings
PublisherInternational Society Offshore & Polar Engineers
Volume4
ISSN (Print)1098-6189

Keywords

  • ANN-based response surface method
  • artificial neural networks
  • response surface method
  • ultimate strength of plates
  • design equations of plates

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