Extracting Three-Dimensional Cellular Automaton for Cement Microstructure Development using Gene Expression Programming

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@InProceedings{Liang:2014:NaBIC,
  author =       "Zhifeng Liang and Bo Yang and Lin Wang and 
                 Xiaoqiang Zhang and Nana He and Ajith Abraham",
  title =        "Extracting Three-Dimensional Cellular Automaton for
                 Cement Microstructure Development using Gene Expression
                 Programming",
  booktitle =    "Sixth World Congress on Nature and Biologically
                 Inspired Computing",
  year =         "2014",
  editor =       "Ana Maria Madureira and Ajith Abraham and 
                 Emilio Corchado and Leonilde Varela and Azah Kamilah Muda and 
                 Choo yun Huoy",
  pages =        "41--46",
  address =      "Porto, Portugal",
  month =        "30 " # jul # " - 1 " # jul,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming: Poster",
  isbn13 =       "978-1-4799-5937-2/14",
  DOI =          "doi:10.1109/NaBIC.2014.6921851",
  abstract =     "A three-dimensional CA model for the simulation of
                 Portland cement microstructure development has been
                 developed in this paper. The Gene Expression
                 Programming (GEP) algorithm is employed as the learning
                 algorithm to evolve the transition rule reversely from
                 the microstructure development characteristic data due
                 to hydration reactions. The characteristic data is
                 extracted from 8-bit gray images that based on the
                 processing of real cement acquired by Micro Computed
                 Tomography (micro-CT) technology. Starting with initial
                 micro-CT image, cement microstructure evolution images
                 of 28 days is constructed through CA rule discovered by
                 GEP. The experimental results show that this model with
                 the CA rule designed by GEP has higher agreement
                 between the model predictions and experimental
                 measurements for degree of hydration than other models.
                 Furthermore, this model still has good generalisation
                 ability when changing the water-cement ratio and
                 chemical composition.",
  notes =        "NaBIC 2014 http://www.mirlabs.net/nabic14/",
}

Genetic Programming entries for Zhifeng Liang Bo Yang Lin Wang Xiaoqiang Zhang Nana He Ajith Abraham

Citations