Genetic programming for moment capacity modeling of ferrocement members
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- @Article{Gandomi:2013:EngStruct,
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author = "Amir H. Gandomi and David A. Roke and Kallol Sett",
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title = "Genetic programming for moment capacity modeling of
ferrocement members",
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journal = "Engineering Structures",
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year = "2013",
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volume = "57",
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pages = "169--176",
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month = dec,
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keywords = "genetic algorithms, genetic programming, gene
expression programming, Moment capacity, Ferrocement
members",
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ISSN = "0141-0296",
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URL = "http://www.sciencedirect.com/science/article/pii/S0141029613004343",
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DOI = "doi:10.1016/j.engstruct.2013.09.022",
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size = "8 pages",
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abstract = "In this study, a robust variant of genetic programming
called gene expression programming (GEP) is used to
predict the moment capacity of ferrocement members.
Constitutive relationships were obtained to correlate
the ultimate moment capacity with mechanical and
geometrical parameters using previously published
experimental results. A subsequent parametric analysis
was carried out and the trends of the results were
confirmed. A comparative study was conducted between
the results obtained by the proposed models and those
of the plastic analysis, mechanism and nonlinear
regression approaches, as well as two black-box models:
back-propagation neural networks (BPNN) and an adaptive
neuro-fuzzy inference system (ANFIS). Three GEP models
are developed to capture the effect of randomising the
test data subsets used to develop the models. The
results indicate that the GEP models accurately
estimate the moment capacity of ferrocement members.
The prediction performance of the GEP models is
significantly better than the plastic analysis,
mechanism and nonlinear regression approaches and is
comparable to that of the BPNN and ANFIS models.",
- }
Genetic Programming entries for
A H Gandomi
David Roke
Kallol Sett
Citations