Genetic modeling of electrical conductivity of formed material
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Gusel:2005:MT,
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author = "Leo Gusel and Miran Brezocnik",
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title = "Genetic modeling of electrical conductivity of formed
material",
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journal = "Materials and technology",
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year = "2005",
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volume = "39",
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number = "4",
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pages = "107--111",
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email = "mbrezocnik@uni-mb.si",
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keywords = "genetic algorithms, genetic programming, copper
alloys, electrical conductivity, cold forming,
modelling, genetsko programiranje, modeliranje, hladno
preoblikovanje, elektricna prevodnost, bakrove
zlitine",
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ISSN = "1580-2949",
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URL = "http://www.imt.si/materiali-tehnologije/",
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URL = "http://ctklj.ctk.uni-lj.si/kovine/izvodi/mit054/gusel.pdf",
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size = "5 pages",
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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.",
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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
Citations