Formulation of soil angle of shearing resistance using a hybrid GP and OLS method
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- @Article{Mousavi:2013:EwC,
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author = "Seyyed Mohammad Mousavi and Amir Hossein Alavi and
Ali Mollahasani and Amir Hossein Gandomi and
Milad {Arab Esmaeili}",
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title = "Formulation of soil angle of shearing resistance using
a hybrid GP and OLS method",
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journal = "Engineering with Computers",
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year = "2013",
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volume = "29",
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number = "1",
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pages = "37--53",
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month = jan,
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keywords = "genetic algorithms, genetic programming, Effective
angle of shearing resistance, Soil physical properties,
Orthogonal least squares, Hybridisation",
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publisher = "Springer",
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language = "English",
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ISSN = "0177-0667",
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URL = "http://link.springer.com/article/10.1007%2Fs00366-011-0242-x",
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DOI = "doi:10.1007/s00366-011-0242-x",
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size = "17 pages",
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abstract = "In the present study, a prediction model was derived
for the effective angle of shearing resistance (phi' )
of soils using a novel hybrid method coupling genetic
programming (GP) and orthogonal least squares algorithm
(OLS). The proposed nonlinear model relates phi to the
basic soil physical properties. A comprehensive
experimental database of consolidated-drained triaxial
tests was used to develop the model. Traditional GP and
least square regression analyses were performed to
benchmark the GP/OLS model against classical
approaches. Validity of the model was verified using a
part of laboratory data that were not involved in the
calibration process. The statistical measures of
correlation coefficient, root mean squared error, and
mean absolute percent error were used to evaluate the
performance of the models. Sensitivity and parametric
analyses were conducted and discussed. The GP/OLS-based
formula precisely estimates the phi' values for a
number of soil samples. The proposed model provides a
better prediction performance than the traditional GP
and regression models.",
- }
Genetic Programming entries for
Seyyed Mohammad Mousavi
A H Alavi
Ali Mollahasani
A H Gandomi
Milad Arab Esmaeili
Citations