Genetic-based modeling of uplift capacity of suction caissons

Created by W.Langdon from gp-bibliography.bib Revision:1.7778

@Article{Alavi2011,

• author = "Amir Hossein Alavi and Pejman Aminian and Amir Hossein Gandomi and Milad {Arab Esmaeili}",
• title = "Genetic-based modeling of uplift capacity of suction caissons",
• journal = "Expert Systems with Applications",
• volume = "38",
• number = "10",
• pages = "12608--12618",
• year = "2011",
• month = "15 " # sep,
• ISSN = "0957-4174",
• URL = "http://www.sciencedirect.com/science/article/pii/S0957417411005653",
• URL = "http://www.sciencedirect.com/science/article/B6V03-52P1KNK-4/2/f33267200d0fc51ad7a086befe3a361c",
• DOI = "doi:10.1016/j.eswa.2011.04.049",
• keywords = "genetic algorithms, genetic programming, Gene expression programming, Suction caissons, Uplift capacity, Formulation",
• size = "11 pages",
• abstract = "In this study, classical tree-based genetic programming (TGP) and its recent variants, namely linear genetic programming (LGP) and gene expression programming (GEP) are used to develop new prediction equations for the uplift capacity of suction caissons. The uplift capacity is formulated in terms of several inflecting variables. An experimental database obtained from the literature is employed to develop the models. Further, a conventional statistical analysis is performed to benchmark the proposed models. Sensitivity and parametric analyses are conducted to verify the results. TGP, LGP and GEP are found to be effective methods for evaluating the horizontal, vertical, and inclined uplift capacity of suction caissons. The TGP, LGP and GEP models reach a prediction performance better than or comparable with the models found in the literature.",

}

Genetic Programming entries for A H Alavi Pejman Aminian A H Gandomi Milad Arab Esmaeili

Citations