A soft computing based approach for the prediction of ultimate strength of metal plates in compression

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@Article{Cevik:2007:ES,
  author =       "Abdulkadir Cevik and Ibrahim H. Guzelbey",
  title =        "A soft computing based approach for the prediction of
                 ultimate strength of metal plates in compression",
  journal =      "Engineering Structures",
  year =         "2007",
  volume =       "29",
  number =       "3",
  pages =        "383--394",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Soft
                 computing, Neural networks, Buckling, Plates",
  DOI =          "doi:10.1016/j.engstruct.2006.05.005",
  abstract =     "This paper presents two plate strength formulations
                 applicable to metals with nonlinear stress-strain
                 curves, such as aluminium and stainless steel alloys,
                 obtained by soft computing techniques, namely Neural
                 Networks (ANN) and Genetic Programming (GP). The
                 proposed soft computing formulations are based on
                 well-defined FE results available in the literature.
                 The proposed formulations enable determination of the
                 buckling strength of rectangular plates in terms of
                 RambergOsgood parameters. The strength curves obtained
                 by the proposed soft computing formulations show
                 perfect agreement with FE results. The formulations are
                 later compared with related codes and results are found
                 to be quite satisfactory.",
}

Genetic Programming entries for Abdulkadir Cevik Ibrahim H Guzelbey

Citations