This paper proposes new approach for modeling of
various processes in metal-forming industry. As an
example, we demonstrate the use of genetic programming
(GP) for modeling of forming efficiency. The forming
efficiency is a basis for determination of yield stress
which is the fundamental characteristic of metallic
materials. Several different genetically evolved models
for forming efficiency on the basis of experimental
data for learning were discovered. The obtained models
(equations) differ in size, shape, complexity and
precision of solutions. In one run out of many runs of
our GP system the well-known equation of Siebel was
obtained. This fact leads us to opinion that GP is a
very powerful evolutionary optimization method
appropriate not only for modeling of forming efficiency
but also for modeling of many other processes in
metal-forming industry.
%0 Journal Article
%1 Brezocnik:2001:MPT
%A Brezocnik, Miran
%A Balic, Joze
%A Kampus, Z.
%D 2001
%J Journal of Materials Processing Technology
%K algorithms, genetic programming
%N 1-2
%P 20--29
%T Modeling of forming efficiency using genetic
programming
%U http://www.sciencedirect.com/science/article/B6TGJ-423HM9M-5/1/bcc93a13fbb04521236d3a8e16f8850b
%V 109
%X This paper proposes new approach for modeling of
various processes in metal-forming industry. As an
example, we demonstrate the use of genetic programming
(GP) for modeling of forming efficiency. The forming
efficiency is a basis for determination of yield stress
which is the fundamental characteristic of metallic
materials. Several different genetically evolved models
for forming efficiency on the basis of experimental
data for learning were discovered. The obtained models
(equations) differ in size, shape, complexity and
precision of solutions. In one run out of many runs of
our GP system the well-known equation of Siebel was
obtained. This fact leads us to opinion that GP is a
very powerful evolutionary optimization method
appropriate not only for modeling of forming efficiency
but also for modeling of many other processes in
metal-forming industry.
@article{Brezocnik:2001:MPT,
abstract = {This paper proposes new approach for modeling of
various processes in metal-forming industry. As an
example, we demonstrate the use of genetic programming
(GP) for modeling of forming efficiency. The forming
efficiency is a basis for determination of yield stress
which is the fundamental characteristic of metallic
materials. Several different genetically evolved models
for forming efficiency on the basis of experimental
data for learning were discovered. The obtained models
(equations) differ in size, shape, complexity and
precision of solutions. In one run out of many runs of
our GP system the well-known equation of Siebel was
obtained. This fact leads us to opinion that GP is a
very powerful evolutionary optimization method
appropriate not only for modeling of forming efficiency
but also for modeling of many other processes in
metal-forming industry.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Brezocnik, Miran and Balic, Joze and Kampus, Z.},
biburl = {https://www.bibsonomy.org/bibtex/2a9503c0ef306dcb597a3d4ddfae7096b/brazovayeye},
interhash = {dd010729a56bcee0fe413392584364c7},
intrahash = {a9503c0ef306dcb597a3d4ddfae7096b},
issn = {0924-0136},
journal = {Journal of Materials Processing Technology},
keywords = {algorithms, genetic programming},
notes = {Journal of Materials Processing Technology
http://www.elsevier.com/wps/find/journaldescription.cws_home/505656/description#description},
number = {1-2},
pages = {20--29},
timestamp = {2008-06-19T17:36:58.000+0200},
title = {Modeling of forming efficiency using genetic
programming},
url = {http://www.sciencedirect.com/science/article/B6TGJ-423HM9M-5/1/bcc93a13fbb04521236d3a8e16f8850b},
volume = 109,
year = 2001
}