Genetic modeling of electrical conductivity of formed material

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@Article{Gusel:2005:MT,
  author =       "Leo Gusel and Miran Brezocnik",
  title =        "Genetic modeling of electrical conductivity of formed
                 material",
  journal =      "Materials and technology",
  year =         "2005",
  volume =       "39",
  number =       "4",
  pages =        "107--111",
  email =        "mbrezocnik@uni-mb.si",
  keywords =     "genetic algorithms, genetic programming, copper
                 alloys, electrical conductivity, cold forming,
                 modelling, genetsko programiranje, modeliranje, hladno
                 preoblikovanje, elektricna prevodnost, bakrove
                 zlitine",
  ISSN =         "1580-2949",
  URL =          "http://www.imt.si/materiali-tehnologije/",
  URL =          "http://ctklj.ctk.uni-lj.si/kovine/izvodi/mit054/gusel.pdf",
  size =         "5 pages",
  abstract =     "In the paper a genetic programming method for
                 efficient determination of accurate models for the
                 change of electrical conductivity of cold formed alloy
                 CuCrZr was presented. The main characteristic of
                 genetic programming method, which is one of
                 evolutionary methods for modelling, is its non-
                 deterministic way of computing. No assumptions about
                 the form and size of expressions were made in advance,
                 but they were left to the self organisation and
                 intelligence of evolutionary process. Only the best
                 models, gained by genetic programming were presented in
                 the paper. Accuracy of the best models was proved with
                 the testing data set. The comparison between deviation
                 of genetic models results and regression models results
                 concerning the experimental results has showed that
                 genetic models are much more precise and more varied
                 then regression model. The variety of genetic models
                 allows us, concerning the demands, to decide for an
                 optimal genetic model for mathematical description and
                 prediction of change of electrical conductivity in the
                 frame of experimental environment.",
  abstract =     "V prispevku smo predstavili metodo genetskega
                 programiranja za uspesno dolocitev natancnih modelov
                 spremembe elektricne prevodnosti hladno preoblikovane
                 zlitine CuCrZr. Glavna znacilnost metode genetskega
                 programiranja, ki spada med evolucijske metode
                 modeliranja, je, da resitev ne iscemo po vnaprej
                 dolocenih poteh ter da socasno obravnavamo mnozico
                 enostavnih objektov. Cedalje natancnejsim resitvam smo
                 se priblizevali postopoma, med postopkom simulirane
                 evolucije. V prispevku smo predstavili le nekatere
                 najuspesnejse oziroma najprimernejse genetske modele.
                 Natancnost genetskih modelov je bila preverjena na
                 mnozici preskusnih tock. Primerjali smo tudi natancnost
                 genetsko dobljenih modelov in modela, dobljenega po
                 deterministicni metodi regresije. Primerjava je
                 pokazala, da se genetski modeli dosti manj odmikajo od
                 eksperimentalnih rezultatov in da so bolj raznoliki.
                 Prav raznolikost nam omogoca, da se, glede na zahteve,
                 odlocimo za optimalen model, s katerim lahko
                 matematicno opisemo ali napovedujemo spremembo
                 elektricne prevodnosti zlitine v okviru
                 eksperimentalnega okolja.",
}

Genetic Programming entries for Leo Gusel Miran Brezocnik

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