A new predictive model for compressive strength of HPC using gene expression programming
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- @Article{journals/aes/MousaviAGAB12,
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author = "Seyyed Mohammad Mousavi and Pejman Aminian and
Amir Hossein Gandomi and Amir Hossein Alavi and
Hamed Bolandi",
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title = "A new predictive model for compressive strength of HPC
using gene expression programming",
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journal = "Advances in Engineering Software",
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year = "2012",
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volume = "45",
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number = "1",
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pages = "105--114",
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month = mar,
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keywords = "genetic algorithms, genetic programming, gene
expression programming, compressive strength,
regression analysis, sensitivity analysis, prediction,
high performance concrete",
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ISSN = "0965-9978",
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URL = "http://www.sciencedirect.com/science/article/pii/S0965997811002535",
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DOI = "doi:10.1016/j.advengsoft.2011.09.014",
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abstract = "In this study, gene expression programming (GEP) is
used to derive a new model for the prediction of
compressive strength of high performance concrete (HPC)
mixes. The model is developed using a comprehensive
database obtained from the literature. The validity of
the proposed model is verified by applying it to
estimate the compressive strength of a portion of test
results that are not included in the analysis. Linear
and nonlinear least squares regression analyses are
performed to benchmark the GEP model. Contributions of
the parameters affecting the compressive strength are
evaluated through a sensitivity analysis. GEP is found
to be an effective method for evaluating the
compressive strength of HPC mixes. The prediction
performance of the optimal GEP model is better than the
regression models.",
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bibdate = "2011-12-31",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/aes/aes45.html#MousaviAGAB12",
- }
Genetic Programming entries for
Seyyed Mohammad Mousavi
Pejman Aminian
A H Gandomi
A H Alavi
Hamed Bolandi
Citations