Predicting stress distribution in cold-formed material with genetic programming

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@Article{Brezocnik:2004:IJAMT,
  author =       "Miran Brezocnik and Leo Gusel",
  title =        "Predicting stress distribution in cold-formed material
                 with genetic programming",
  journal =      "International journal of advanced manufacturing
                 technology",
  year =         "2004",
  volume =       "23",
  number =       "7-8",
  pages =        "467--474",
  email =        "mbrezocnik@uni-mb.si",
  keywords =     "genetic algorithms, genetic programming, metal
                 forming, stress distribution, modelling",
  ISSN =         "0268-3768",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0268-3768&volume=23&issue=7&spage=467",
  DOI =          "doi:10.1007/s00170-003-1649-3",
  abstract =     "In this paper we propose a genetic programming
                 approach to predict radial stress distribution in
                 cold-formed material. As an example, cylindrical
                 specimens of copper alloy were forward extruded and
                 analysed by the visioplasticity method. They were
                 extruded with different coefficients of friction. The
                 values of three independent variables (i.e., radial and
                 axial position of measured stress node, and coefficient
                 of friction) were collected after each extrusion. These
                 variables influence the value of the dependent
                 variable, i.e., radial stress. On the basis of training
                 data set, various different prediction models for
                 radial stress distribution were developed during
                 simulated evolution. Accuracy of the best models was
                 proved with the testing data set. The research showed
                 that by proposed approach the precise prediction models
                 can be developed; therefore, it is widely used also in
                 other areas in metal-forming industry, where the
                 experimental data on the process are known.",
}

Genetic Programming entries for Miran Brezocnik Leo Gusel

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