Genetic programming and orthogonal least squares: a hybrid approach to modeling the compressive strength of CFRP-confined concrete cylinders
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- @Article{Gandomi:2010:JMMS,
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author = "Amir Hossein Gandomi and Amir Hossein Alavi and
Parvin Arjmandi and Alireza Aghaeifar and Reza Seyednour",
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title = "Genetic programming and orthogonal least squares: a
hybrid approach to modeling the compressive strength of
{CFRP-confined} concrete cylinders",
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journal = "Journal of Mechanics of Materials and Structures",
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year = "2010",
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volume = "5",
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number = "5",
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pages = "735--753",
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keywords = "genetic algorithms, genetic programming, orthogonal
least squares, CFRP confinement, concrete compressive
strength, formulation",
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publisher = "Mathematical Sciences Publishers",
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ISSN = "1559-3959",
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URL = "http://msp.org/jomms/2010/5-5/p03.xhtml",
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DOI = "doi:10.2140/jomms.2010.5.735",
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size = "19 pages",
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abstract = "The main objective of this paper is to apply genetic
programming (GP) with an orthogonal least squares (OLS)
algorithm to derive a predictive model for the
compressive strength of carbon fibre-reinforced plastic
(CFRP) confined concrete cylinders. The GP/OLS model
was developed based on experimental results obtained
from the literature. Traditional GP-based and least
squares regression analyses were performed using the
same variables and data sets to benchmark the GP/OLS
model. A subsequent parametric analysis was carried out
and the trends of the results were confirmed via
previous laboratory studies. The results indicate that
the proposed formula can predict the ultimate
compressive strength of concrete cylinders with an
acceptable level of accuracy. The GP/OLS results are
more accurate than those obtained using GP, regression,
or several CFRP confinement models found in the
literature. The GP/OLS-based formula is simple and
straightforward, and provides a valuable tool for
analysis.",
- }
Genetic Programming entries for
A H Gandomi
A H Alavi
Parvin Arjmandi
Alireza Aghaeifar
Reza Seyednour
Citations