Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

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@Article{Bayazidi:2014:MPiE,

• author = "Alireza Mohammadi Bayazidi and Gai-Ge Wang and Hamed Bolandi and Amir H. Alavi and Amir H. Gandomi",
• title = "Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete",
• journal = "Mathematical Problems in Engineering",
• year = "2014",
• keywords = "genetic algorithms, genetic programming",
• publisher = "Hindawi",
• URL = "http://dx.doi.org/10.1155/2014/474289",
• DOI = "doi:10.1155/2014/474289",
• size = "10 pages",
• abstract = "This paper presents a new multigene genetic programming (MGGP) approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behaviour by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalised prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools.",
• notes = "Article ID 474289",

}

Genetic Programming entries for Alireza Mohammadi Bayazidi Gai-Ge Wang Hamed Bolandi A H Alavi A H Gandomi

Citations