Improving analytical models of circular concrete columns with genetic programming polynomials

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@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

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