Prediction of compressive and tensile strength of limestone via genetic programming
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- @Article{Baykasoglu2008111,
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author = "Adil Baykasoglu and Hamza Gullu and Hanifi Canakci and
Lale Ozbakir",
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title = "Prediction of compressive and tensile strength of
limestone via genetic programming",
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journal = "Expert Systems with Applications",
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year = "2008",
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volume = "35",
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number = "1-2",
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pages = "111--123",
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month = jul # "-" # aug,
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keywords = "genetic algorithms, genetic programming, multi
expression programming, gene expression programming,
Prediction, Limestone, Strength of materials",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2007.06.006",
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broken = "http://www.sciencedirect.com/science/article/B6V03-4NYJ0NK-1/2/00b6bf799aaf3df77a5e0fd846b85f20",
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abstract = "Accurate determination of compressive and tensile
strength of limestone is an important subject for the
design of geotechnical structures. Although there are
several classical approaches in the literature for
strength prediction their predictive accuracy is
generally not satisfactory. The trend in the literature
is to apply artificial intelligence based soft
computing techniques for complex prediction problems.
Artificial neural networks which are a member of soft
computing techniques were applied to strength
prediction of several types of rocks in the literature
with considerable success. Although artificial neural
networks are successful in prediction, their inability
to explicitly produce prediction equations can create
difficulty in practical circumstances. Another member
of soft computing family which is known as genetic
programming can be a very useful candidate to overcome
this problem. Genetic programming based approaches are
not yet applied to the strength prediction of
limestone. This paper makes an attempt to apply a
promising set of genetic programming techniques which
are known as multi expression programming (MEP), gene
expression programming (GEP) and linear genetic
programming (LGP) to the uniaxial compressive strength
(UCS) and tensile strength prediction of chalky and
clayey soft limestone. The data for strength prediction
were generated experimentally in the University of
Gaziantep civil engineering laboratories by using
limestone samples collected from Gaziantep region of
Turkey.",
- }
Genetic Programming entries for
Adil Baykasoglu
Hamza Gullu
Hanifi Canakci
Lale Ozbakir
Citations