Leo Gusel (Author), Miran Brezočnik (Author)

Abstract

V prispevku smo predstavili metodo genetskega programiranja za uspešno določitev natančnih modelov spremembe električne prevodnosti hladno preoblikovane zlitine CuCrZr. Glavna značilnost metode genetskega programiranja, ki spada med evolucijske metode modeliranja, je, da rešitev ne iščemo po vnaprej določenih poteh ter da sočasno obravnavamo množico enostavnih objektov. Čedalje natančnejšim rešitvam smo se približevali postopoma, med postopkom simulirane evolucije. V prispevku smo predstavili le nekatere najuspešnejše oziroma najprimernejše genetske modele. Natančnost genetskih modelov je bila preverjena na množici preskusnih točk. Primerjali smo tudi natančnost genetsko dobljenih modelov in modela, dobljenega po deterministični metodi regresije. Primerjava je pokazala, da se genetski modeli dosti manj odmikajo od eksperimentalnih rezultatov in da so bolj raznoliki. Prav raznolikost nam omogoča, da se, glede na zahteve, odločimo za optimalen model, s katerim lahko matematično opišemo ali napovedujemo spremembo električne prevodnosti zlitine v okviru eksperimentalnega okolja.

Keywords

genetsko programiranje;modeliranje;hladno preoblikovanje;električna prevodnost;bakrove zlitine;

Data

Language: Slovenian
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FS - Faculty of Mechanical Engineering
Publisher: Inštitut za kovinske materiale in tehnologije
UDC: 669.3:537.24:621.7
COBISS: 9781782 Link will open in a new window
ISSN: 1580-2949
Views: 1117
Downloads: 81
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Other data

Secondary language: English
Secondary title: Genetic modeling of electrical conductivity of formed material
Secondary 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 modeling, 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 organization 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.
Secondary keywords: genetic programming;modeling;cold forming;electrical conductivity;copper alloys;
URN: URN:NBN:SI
Type (COBISS): Scientific work
Pages: str. 107-111
Volume: ǂLetn. ǂ39
Issue: ǂšt. ǂ4
Chronology: 2005
ID: 1743160