A hybrid computational approach to formulate soil deformation moduli obtained from PLT
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- @Article{Mousavi2011324,
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author = "Seyyed Mohammad Mousavi and Amir Hossein Alavi and
Ali Mollahasani and Amir Hossein Gandomi",
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title = "A hybrid computational approach to formulate soil
deformation moduli obtained from PLT",
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journal = "Engineering Geology",
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volume = "123",
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number = "4",
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pages = "324--332",
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year = "2011",
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ISSN = "0013-7952",
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DOI = "doi:10.1016/j.enggeo.2011.09.005",
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URL = "http://www.sciencedirect.com/science/article/pii/S0013795211002183",
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keywords = "genetic algorithms, genetic programming, Soil
deformation moduli, Soil physical properties, Simulated
annealing, Nonlinear modelling",
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abstract = "In this study, new empirical equations were developed
to predict the soil deformation moduli using a hybrid
method coupling genetic programming and simulated
annealing, called GP/SA. The proposed models relate
secant (Es), unloading (Eu) and reloading (Er) moduli
obtained from plate load-settlement curves to the basic
soil physical properties. Several models with different
combinations of the influencing parameters were
developed and checked to select the best GP/SA models.
The database used for developing the models was
established upon a series of plate load tests (PLT)
conducted on different soil types at various depths.
The validity of the models was tested using parts of
the test results that were not included in the
analysis. The validation of the models was further
verified using several statistical criteria. A
traditional GP analysis was performed to benchmark the
GP/SA models. The contributions of the parameters
affecting Es, Eu and Er were analysed through a
sensitivity analysis. The proposed models are able to
estimate the soil deformation moduli with an acceptable
degree of accuracy. The Es prediction model has a
remarkably better performance than the models developed
for predicting Eu and Er. The simplified formulations
for Es, Eu and Er provide significantly better results
than the GP-based models and empirical models found in
the literature.",
- }
Genetic Programming entries for
Seyyed Mohammad Mousavi
A H Alavi
Ali Mollahasani
A H Gandomi
Citations