%0 Journal Article %1 Gusel:2005:MT %A Gusel, Leo %A Brezocnik, Miran %D 2005 %J Materials and technology %K algorithms, alloys, bakrove cold conductivity, copper electrical elektricna forming, genetic genetsko hladno modeliranje, modelling, preoblikovanje, prevodnost, programiranje, programming, zlitine %N 4 %P 107--111 %T Genetic modeling of electrical conductivity of formed material %U http://ctklj.ctk.uni-lj.si/kovine/izvodi/mit054/gusel.pdf %V 39 %X 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.

@article{Gusel:2005:MT, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Gusel, Leo and Brezocnik, Miran}, biburl = {https://www.bibsonomy.org/bibtex/26e812fbca3461fe4e7511f1fc6dd68a0/brazovayeye}, email = {mbrezocnik@uni-mb.si}, interhash = {52426783609b29d259dbb1f17d0ecc4f}, intrahash = {6e812fbca3461fe4e7511f1fc6dd68a0}, issn = {1580-2949}, journal = {Materials and technology}, keywords = {algorithms, alloys, bakrove cold conductivity, copper electrical elektricna forming, genetic genetsko hladno modeliranje, modelling, preoblikovanje, prevodnost, programiranje, programming, zlitine}, number = 4, pages = {107--111}, size = {5 pages}, timestamp = {2008-06-19T17:40:45.000+0200}, title = {Genetic modeling of electrical conductivity of formed material}, url = {http://ctklj.ctk.uni-lj.si/kovine/izvodi/mit054/gusel.pdf}, volume = 39, year = 2005 }