%0 Journal Article %1 Gusel:2006:CMS %A Gusel, Leo %A Brezocnik, Miran %D 2006 %J Computational Materials Science %K algorithms, alloy computing, copper evolutionary forming, genetic impact metal modelling, programming, toughness, %N 4 %P 476--482 %R doi:10.1016/j.commatsci.2005.11.007 %T Modeling of impact toughness of cold formed material by genetic programming %V 37 %X In the paper, an approach completely different from the conventional methods for determination of accurate models for the change of properties of cold formed material, is presented. This approach is genetic programming (GP) method which is based on imitation of natural evolution of living organisms. The main characteristic of GP 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. First, copper alloy rods were cold drawn under different conditions and then impact toughness of cold drawn specimens was determined by Charpy tests. The values of independent variables (effective strain, coefficient of friction) influence the value of the dependent variable, impact toughness. On the basis of training data, different prediction models for impact toughness were developed by GP. 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 model results and regression model results concerning the experimental results has showed that genetic models are more precise and more varied then regression models.

@article{Gusel:2006:CMS, abstract = {In the paper, an approach completely different from the conventional methods for determination of accurate models for the change of properties of cold formed material, is presented. This approach is genetic programming (GP) method which is based on imitation of natural evolution of living organisms. The main characteristic of GP 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. First, copper alloy rods were cold drawn under different conditions and then impact toughness of cold drawn specimens was determined by Charpy tests. The values of independent variables (effective strain, coefficient of friction) influence the value of the dependent variable, impact toughness. On the basis of training data, different prediction models for impact toughness were developed by GP. 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 model results and regression model results concerning the experimental results has showed that genetic models are more precise and more varied then regression models.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Gusel, Leo and Brezocnik, Miran}, biburl = {https://www.bibsonomy.org/bibtex/2433c0f419dab96f94c8f385cc055e99c/brazovayeye}, doi = {doi:10.1016/j.commatsci.2005.11.007}, email = {mbrezocnik@uni-mb.si}, interhash = {2639f96f679d445aaae67228013ff9aa}, intrahash = {433c0f419dab96f94c8f385cc055e99c}, issn = {0927-0256}, journal = {Computational Materials Science}, keywords = {algorithms, alloy computing, copper evolutionary forming, genetic impact metal modelling, programming, toughness,}, month = {October}, number = 4, pages = {476--482}, timestamp = {2008-06-19T17:40:46.000+0200}, title = {Modeling of impact toughness of cold formed material by genetic programming}, volume = 37, year = 2006 }