Improving analytical models of circular concrete columns with genetic programming polynomials

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Tsai:2013:GPEM,
  author =       "Hsing-Chih Tsai and Chan-Ping Pan",
  title =        "Improving analytical models of circular concrete
                 columns with genetic programming polynomials",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2013",
  volume =       "14",
  number =       "2",
  pages =        "221--243",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Models,
                 Compressive strength, Strain, Concrete columns,
                 Polynomials",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-012-9176-3",
  size =         "23 pages",
  abstract =     "This study improves weighted genetic programming and
                 uses proposed novel genetic programming polynomials
                 (GPP) for accurate prediction and visible
                 formulae/polynomials. Representing confined compressive
                 strength and strain of circular concrete columns in
                 meaningful representations makes parameter studies,
                 sensitivity analysis, and application of pruning
                 techniques easy. Furthermore, the proposed GPP is used
                 to improve existing analytical models of circular
                 concrete columns. Analytical results demonstrate that
                 the GPP performs well in prediction accuracy and
                 provides simple polynomials as well. Three identified
                 parameters improve the analytical models the lateral
                 steel ratio improves both compressive strength and
                 strain of the target models of circular concrete
                 columns; compressive strength of unconfined concrete
                 specimen improves the strength equation; and tie
                 spacing improves the strain equation.",
}

Genetic Programming entries for Hsing-Chih Tsai Chan-Ping Pan

Citations