Predicting torsional strength of RC beams by using Evolutionary Polynomial Regression

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@Article{Fiore2012178,
  author =       "Alessandra Fiore and Luigi Berardi and 
                 Giuseppe Carlo Marano",
  title =        "Predicting torsional strength of RC beams by using
                 Evolutionary Polynomial Regression",
  journal =      "Advances in Engineering Software",
  volume =       "47",
  number =       "1",
  pages =        "178--187",
  year =         "2012",
  ISSN =         "0965-9978",
  DOI =          "doi:10.1016/j.advengsoft.2011.11.001",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0965997811003036",
  keywords =     "genetic algorithms, genetic programming, Reinforced
                 concrete beam, Evolutionary Polynomial Regression,
                 Torsional strength, Building code, Theoretical model,
                 Soft computing",
  abstract =     "A new view for the analytical formulation of torsional
                 ultimate strength for reinforced concrete (RC) beams by
                 experimental data is explored by using a new hybrid
                 regression method termed Evolutionary Polynomial
                 Regression (EPR). In the case of torsion in RC
                 elements, the poor assumptions in physical models often
                 result into poor agreement with experimental results.
                 Nonetheless, existing models have simple and compact
                 mathematical expressions since they are used by
                 practitioners as building codes provisions.

                 EPR combines the best features of conventional
                 numerical regression techniques with the effectiveness
                 of genetic programming for constructing symbolic
                 expressions of regression models. The EPR modelling
                 paradigm allows to figure out existing patterns in
                 recorded data in terms of compact mathematical
                 expressions, according to the available physical
                 knowledge on the phenomenon (if any). The procedure
                 output is represented by different formulae to predict
                 torsional strength of RC beam. The multi-objective
                 search paradigm used by EPR allows developing a set of
                 formulae showing different complexity of mathematical
                 expressions as resulting into different agreement with
                 experimental data.

                 The efficiency of such approach is tested using
                 experimental data of 64 rectangular RC beams reported
                 in technical literature. The input parameters affecting
                 the torsional strength were selected as cross-sectional
                 area of beams, cross-sectional area of one-leg of
                 closed stirrup, spacing of stirrups, area of
                 longitudinal reinforcement, yield strength of stirrup
                 and longitudinal reinforcement, concrete compressive
                 strength.

                 Those results are finally compared with previous
                 studies and existing building codes for a complete
                 comparison considering formulation complexity and
                 experimental data fitting.",
}

Genetic Programming entries for Alessandra Fiore Luigi Berardi Giuseppe Carlo Marano

Citations