Application of Genetic Programming for Uniaxial and Multiaxial Modeling of Concrete

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{Babanajad:2015:hbgpa,
  author =       "Saeed K. Babanajad",
  title =        "Application of Genetic Programming for Uniaxial and
                 Multiaxial Modeling of Concrete",
  booktitle =    "Handbook of Genetic Programming Applications",
  publisher =    "Springer",
  year =         "2015",
  editor =       "Amir H. Gandomi and Amir H. Alavi and Conor Ryan",
  chapter =      "16",
  pages =        "399--430",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-20882-4",
  DOI =          "doi:10.1007/978-3-319-20883-1_16",
  abstract =     "In current chapter, an overview of recently
                 established genetic programming based techniques for
                 strength modelling of concrete has been presented. The
                 comprehensive uniaxial and multiaxial strengths
                 modelling of hardened concrete have been concentrated
                 in this chapter as one of the main area of interests in
                 concrete modeling for structural engineers. For this
                 engineering case the literature has been reviewed and
                 the most applied numerical/analytical/experimental
                 models and national building codes have been
                 introduced. After reviewing the artificial
                 intelligence/machine learning based models, genetic
                 programming based models are presented, with accent on
                 the applicability and efficiency of each model and its
                 suitability. The advantages and weaknesses of the
                 aforementioned models are summarized and compared with
                 existing numerical/analytical/experimental models and
                 national building codes, and a few illustrative
                 examples briefly are presented. The genetic programming
                 based techniques are remarkably straightforward and
                 have enabled reliable, stable, and robust tools for
                 pre-design and design applications.",
}

Genetic Programming entries for Saeed K Babanajad

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