A Methodology for Combining Symbolic Regression and Design of Experiments to Improve Empirical Model Building

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Castillo:2003:gecco,
  author =       "Flor Castillo and Kenric Marshall and James Green and 
                 Arthur Kordon",
  title =        "A Methodology for Combining Symbolic Regression and
                 Design of Experiments to Improve Empirical Model
                 Building",
  booktitle =    "Genetic and Evolutionary Computation -- GECCO-2003",
  editor =       "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and 
                 D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and 
                 R. Standish and G. Kendall and S. Wilson and 
                 M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and 
                 A. C. Schultz and K. Dowsland and N. Jonoska and 
                 J. Miller",
  year =         "2003",
  pages =        "1975--1985",
  address =      "Chicago",
  publisher_address = "Berlin",
  month =        "12-16 " # jul,
  volume =       "2724",
  series =       "LNCS",
  ISBN =         "3-540-40603-4",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, symbolic
                 regression, design of experiments, Real World
                 Applications",
  DOI =          "doi:10.1007/3-540-45110-2_96",
  abstract =     "A novel methodology for empirical model building using
                 GP-generated symbolic regression in combination with
                 statistical design of experiments as well as undesigned
                 data is proposed. The main advantage of this
                 methodology is the maximum data usage when
                 extrapolation is necessary. The methodology offers
                 alternative non-linear models that can either linearize
                 the response in the presence of Lack or Fit or
                 challenge and confirm the results from the linear
                 regression in a cost effective and time efficient
                 fashion. The economic benefit is the reduced number of
                 additional experiments in the presence of Lack of
                 Fit.",
  notes =        "GECCO-2003. A joint meeting of the twelfth
                 International Conference on Genetic Algorithms
                 (ICGA-2003) and the eights Annual Genetic Programming
                 Conference (GP-2003)",
}

Genetic Programming entries for Flor A Castillo Kenric A Marshall James Green Arthur K Kordon

Citations