Modeling of Compressive Strength of HPC Mixes Using a Combined Algorithm of Genetic Programming and Orthogonal Least Squares
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- @Article{Mousavi:2010:StruEngMech,
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author = "S. M. Mousavi and A. H. Gandomi and A. H. Alavi and
M. Vesalimahmood",
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title = "Modeling of Compressive Strength of HPC Mixes Using a
Combined Algorithm of Genetic Programming and
Orthogonal Least Squares",
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journal = "Structural Engineering and Mechanics",
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year = "2010",
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volume = "36",
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number = "2",
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pages = "225--241",
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month = sep # " 30",
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keywords = "genetic algorithms, genetic programming, high
performance concrete, orthogonal least square,
compressive strength, formulation",
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URL = "http://technopress.kaist.ac.kr/?page=container&journal=sem&volume=36&num=2",
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DOI = "doi:10.12989/sem.2010.36.2.225",
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abstract = "In this study, a hybrid search algorithm combining
genetic programming with orthogonal least squares
(GP/OLS) is used to generate prediction models for
compressive strength of high performance concrete (HPC)
mixes. The GP/OLS models are developed based on a
comprehensive database containing 1133 experimental
test results obtained from previously published papers.
A multiple least squares regression (LSR) analysis is
performed to benchmark the GP/OLS models. A subsequent
parametric study is carried out to verify the validity
of the models. The results indicate that the proposed
models are effectively capable of evaluating the
compressive strength of HPC mixes. The derived formulae
are very simple, straightforward and provide an
analysis tool accessible to practicing engineers.",
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notes = "SEM",
- }
Genetic Programming entries for
Seyyed Mohammad Mousavi
A H Gandomi
A H Alavi
Majid Vesali Mahmood
Citations