New prediction models for unconfined compressive strength of geopolymer stabilized soil using multi-gen genetic programming
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- @Article{SOLEIMANI:2018:Measurement,
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author = "Sepehr Soleimani and Shabnam Rajaei and
Pengcheng Jiao and Arash Sabz and Sina Soheilinia",
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title = "New prediction models for unconfined compressive
strength of geopolymer stabilized soil using multi-gen
genetic programming",
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journal = "Measurement",
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volume = "113",
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pages = "99--107",
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year = "2018",
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keywords = "genetic algorithms, genetic programming, Soil
stabilization, Geopolymer, Prediction",
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ISSN = "0263-2241",
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DOI = "doi:10.1016/j.measurement.2017.08.043",
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URL = "http://www.sciencedirect.com/science/article/pii/S0263224117305511",
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abstract = "This study presents new models for the prediction of
unconfined compressive strength (UCS) of geopolymer
stabilized clayey soils using a modified branch of
genetic programming, called multi-gen genetic
programming (MGGP). The proposed MGGP models
incorporate several parameters affecting the behavior
of the UCS of the clayey stabilized soil. UCS is
formulated in terms of percentages of fly ash, ground
granulated blast furnace slag, liquid limit, plastic
limit, plasticity index, molar concentration, alkali to
binder ratio, and ratios of sodium and silicon to
aluminum. The importance of each predictor variable is
measured through a sensitivity analysis. The validity
of the models and the trend of the results are verified
by performing parametric study. The parametric study
results are also in good agreement with previous
studies. The results indicate that the proposed
equations are capable of evaluating UCS accurately",
- }
Genetic Programming entries for
Sepehr Soleimani
Shabnam Rajaei
Pengcheng Jiao
Arash Sabz
Sina Soheilinia
Citations