Modelling damping ratio and shear modulus of sand-mica mixtures using genetic programming

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@Article{Cevik2008:ESwA1,

• author = "Abdulkadir Cevik and Ali Firat Cabalar",
• title = "Modelling damping ratio and shear modulus of sand-mica mixtures using genetic programming",
• journal = "Expert Systems with Applications",
• year = "2009",
• volume = "36",
• number = "4",
• pages = "7749--7757",
• month = may,
• keywords = "genetic algorithms, genetic programming, Leighton Buzzard sand, Mica, Resonant column testing",
• ISSN = "0957-4174",
• URL = "http://www.sciencedirect.com/science/article/B6V03-4TGHN90-2/2/78164c859cf3127425aedcca7e6f7d21",
• DOI = "doi:10.1016/j.eswa.2008.09.010",
• size = "9 pages",
• abstract = "This study presents two Genetic Programming (GP) models for damping ratio and shear modulus of sand-mica mixtures based on experimental results. The experimental database used for GP modeling is based on a laboratory study of dynamic properties of saturated coarse rotund sand and mica mixtures with various mix ratios under different effective stresses. In the tests, shear modulus, and damping ratio of the geomaterials have been measured for a strain range of 0.001% up to 0.1% using a Stokoe resonant column testing apparatus. The input variables in the developed NN models are the mica content, effective stress and strain, and the outputs are damping ratio and shear modulus. The performance of accuracies of proposed NN models are quite satisfactory (R2=0.95 for damping ratio and R2=0.98 for shear modulus).",

}

Genetic Programming entries for Abdulkadir Cevik Ali Firat Cabalar

Citations