Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systems

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@Article{Alavi:2014:NCA,

• author = "Amir Hossein Alavi and Amir Hossein Gandomi and Hadi {Chahkandi Nejad} and Ali Mollahasani and Azadeh Rashed",
• title = "Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systems",
• journal = "Neural Computing and Applications",
• year = "2013",
• volume = "23",
• number = "6",
• pages = "1771--1786",
• month = nov,
• keywords = "genetic algorithms, genetic programming, gene expression programming, Soil deformation modulus, Expression programming techniques, Pressure meter test, Soil physical properties",
• publisher = "Springer-Verlag",
• ISSN = "0941-0643",
• URL = "http://link.springer.com/article/10.1007%2Fs00521-012-1144-6",
• DOI = "doi:10.1007/s00521-012-1144-6",
• language = "English",
• size = "16 pages",
• abstract = "Providing precise estimations of soil deformation modulus is very difficult due to its dependence on many factors. In this study, gene expression programming (GEP) and multi-expression programming (MEP) systems are presented to derive empirical equations for the prediction of the pressuremeter soil deformation modulus. The employed expression programming (EP) systems formulate the soil deformation modulus in terms of the soil physical properties. Selection of the best models is on the basis of developing and controlling several models with different combinations of the affecting parameters. The proposed EP-based models are established upon 114 pressure meter tests on different soil types conducted in this study. The generalisation capabilities of the models are verified using several statistical criteria. Contributions of the variables influencing the soil modulus are evaluated through a sensitivity analysis. The GEP and MEP approaches accurately characterise the soil deformation modulus resulting in a very good prediction performance. The result indicates that moisture content and soil dry unit weight can efficiently represent the initial state and consolidation history of soil for determining its modulus.",

}

Genetic Programming entries for A H Alavi A H Gandomi Hadi Chahkandi Nejad Ali Mollahasani Azadeh Rashed

Citations