Nonlinear modeling of shear strength of SFRC beams using linear genetic programming
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- @Article{Gandomi:2011:SEM,
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author = "A. H. Gandomi and A. H. Alavi and G. J. Yun",
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title = "Nonlinear modeling of shear strength of {SFRC} beams
using linear genetic programming",
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journal = "Structural Engineering and Mechanics, An International
Journal",
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year = "2011",
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volume = "38",
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number = "1",
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pages = "1--25",
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month = apr # " 10",
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keywords = "genetic algorithms, genetic programming,
fiber-reinforced concrete beams, linear genetic
programming, SFRC beam, shear strength, formulation.",
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publisher = "Techno Press, P.O. Box 33, Yuseong, Daejeon 305-600
Korea",
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ISSN = "1225-4568",
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URL = "http://technopress.kaist.ac.kr/?page=container&journal=sem&volume=38&num=1",
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DOI = "doi:10.12989/sem.2011.38.1.001",
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abstract = "A new nonlinear model was developed to evaluate the
shear resistance of steel fibre reinforced concrete
beams (SFRCB) using linear genetic programming (LGP).
The proposed model relates the shear strength to the
geometrical and mechanical properties of SFRCB. The
best model was selected after developing and
controlling several models with different combinations
of the influencing parameters. The models were
developed using a comprehensive database containing 213
test results of SFRC beams without stirrups obtained
through an extensive literature review. The database
includes experimental results for normal and
high-strength concrete beams. To verify the
applicability of the proposed model, it was employed to
estimate the shear strength of a part of test results
that were not included in the modelling process. The
external validation of the model was further verified
using several statistical criteria recommended by
researchers. The contributions of the parameters
affecting the shear strength were evaluated through a
sensitivity analysis. The results indicate that the LGP
model gives precise estimates of the shear strength of
SFRCB. The prediction performance of the model is
significantly better than several solutions found in
the literature. The LGP-based design equation is
remarkably straightforward and useful for pre-design
applications.",
- }
Genetic Programming entries for
A H Gandomi
A H Alavi
Gunjin Yun
Citations