Parametric and non-parametric identification of
macro-mechanical models
M. Sebag, M. Schoenauer, and H. Maitournam. Genetic Algorithms and Evolution Strategies in
Engineering and Computer Sciences, page 327--340. John Wiley, (1997)
Abstract
This paper presents evolutionary identification of a
particular form of behavioral laws for
elasto-visco-plastic materials termed rheological
models. First, rheologicalmodels with known graph of
connections are used, and the identification amounts to
identifying real-valued parameters. But the more
challenging task of identifying also thetopology of the
rheological model can be tackled using Genetic
Programming, after turning those models into
parse-trees. Both approaches are compared and discussed
ona simple artificial example.
%0 Conference Paper
%1 SebSch97
%A Sebag, M.
%A Schoenauer, M.
%A Maitournam, H.
%B Genetic Algorithms and Evolution Strategies in
Engineering and Computer Sciences
%D 1997
%E Quagliarella, D.
%E Periaux, J.
%E Poloni, C.
%E Winter, G.
%I John Wiley
%K algorithms, genetic mechanics programming, strutural
%P 327--340
%T Parametric and non-parametric identification of
macro-mechanical models
%U http://www.amazon.com/exec/obidos/ASIN/0471977101/qid%3D977328943/sr%3D1-1/002-5868922-2651240
%X This paper presents evolutionary identification of a
particular form of behavioral laws for
elasto-visco-plastic materials termed rheological
models. First, rheologicalmodels with known graph of
connections are used, and the identification amounts to
identifying real-valued parameters. But the more
challenging task of identifying also thetopology of the
rheological model can be tackled using Genetic
Programming, after turning those models into
parse-trees. Both approaches are compared and discussed
ona simple artificial example.
%@ 0-471-97710-1
@inproceedings{SebSch97,
abstract = {This paper presents evolutionary identification of a
particular form of behavioral laws for
elasto-visco-plastic materials termed rheological
models. First, rheologicalmodels with known graph of
connections are used, and the identification amounts to
identifying real-valued parameters. But the more
challenging task of identifying also thetopology of the
rheological model can be tackled using Genetic
Programming, after turning those models into
parse-trees. Both approaches are compared and discussed
ona simple artificial example.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Sebag, M. and Schoenauer, M. and Maitournam, H.},
biburl = {https://www.bibsonomy.org/bibtex/2a9537ecd5bf5abe14547a14831d1cc98/brazovayeye},
booktitle = {Genetic Algorithms and Evolution Strategies in
Engineering and Computer Sciences},
editor = {Quagliarella, D. and Periaux, J. and Poloni, C. and Winter, G.},
interhash = {11068e595647e0952a52032662b430b2},
intrahash = {a9537ecd5bf5abe14547a14831d1cc98},
isbn = {0-471-97710-1},
keywords = {algorithms, genetic mechanics programming, strutural},
notes = {EUROGEN 1997
abstract not as Wiley book},
organisation = {INGENET},
pages = {327--340},
publisher = {John Wiley},
timestamp = {2008-06-19T17:51:16.000+0200},
title = {Parametric and non-parametric identification of
macro-mechanical models},
url = {http://www.amazon.com/exec/obidos/ASIN/0471977101/qid%3D977328943/sr%3D1-1/002-5868922-2651240},
year = 1997
}