Industrial Strength Genetic Programming

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

@InCollection{kotanchek:2003:GPTP,
  author =       "Mark Kotanchek and Guido Smits and Arthur Kordon",
  title =        "Industrial Strength Genetic Programming",
  booktitle =    "Genetic Programming Theory and Practice",
  publisher =    "Kluwer",
  year =         "2003",
  editor =       "Rick L. Riolo and Bill Worzel",
  chapter =      "15",
  pages =        "239--255",
  keywords =     "genetic algorithms, genetic programming, Empirical
                 Modeling, Symbolic Regression, Support Vector Machines,
                 SVM, ANN, Neural Networks",
  ISBN =         "1-4020-7581-2",
  URL =          "http://www.springer.com/computer/ai/book/978-1-4020-7581-0",
  URL =          "http://www.evolved-analytics.com/.../GPTP03_IndustrialGP_Preprint.pdf",
  DOI =          "doi:10.1007/978-1-4419-8983-3_15",
  abstract =     "Since the mid-1990's, symbolic regression via genetic
                 programming (GP) has become a core component of a
                 multi-disciplinary approach to empirical modeling at
                 Dow Chemical. Herein we review the role of symbolic
                 regression within an integrated empirical modeling
                 methodology, discuss symbolic regression system design
                 issues, best practices and lessons learned from
                 industrial application, and present future directions
                 for research and application",
  notes =        "In theory, there is no difference between theory and
                 practice. In practice, there is. -- Jan L.A. van de
                 Snepscheut

                 Dowchemical Part of \cite{RioloWorzel:2003}",
  size =         "18 pages",
}

Genetic Programming entries for Mark Kotanchek Guido F Smits Arthur K Kordon

Citations