Genetic programming for predicting aseismic abilities of school buildings

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@Article{Chen2012,
  author =       "Hung-Ming Chen2 and Wei-Ko Kao and Hsing-Chih Tsai",
  title =        "Genetic programming for predicting aseismic abilities
                 of school buildings",
  journal =      "Engineering Applications of Artificial Intelligence",
  volume =       "25",
  number =       "6",
  pages =        "1103--1113",
  year =         "2012",
  ISSN =         "0952-1976",
  DOI =          "doi:10.1016/j.engappai.2012.04.002",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0952197612000905",
  keywords =     "genetic algorithms, genetic programming, Prediction,
                 Aseismic ability, School building, Soft computing",
  abstract =     "In general, the aseismic ability of buildings is
                 analysed using nonlinear models. To obtain aseismic
                 abilities of buildings, numerical models are
                 constructed based on the structural configuration and
                 material properties of buildings, and their stress
                 responses and behaviours are simulated. This method is
                 complex, time-consuming, and should only be conducted
                 by professionals. In the past, soft computing
                 techniques have been applied in the construction field
                 to predict the particular stress responses and
                 behaviors; however, only a few studies have been made
                 to predict specific properties of entire buildings. In
                 this study, a weighted genetic programming system is
                 developed to construct the relation models between the
                 aseismic capacity of school buildings, and their basic
                 design parameters. This is based on information from
                 the database of school buildings, as well as
                 information regarding the aseismic capacity of school
                 buildings analysed using complete nonlinear methods.
                 This system can be further applied to predict the
                 aseismic capacity of the school buildings.",
}

Genetic Programming entries for Hung-Ming Chen2 Wei-Ko Kao Hsing-Chih Tsai

Citations