Using Genetic Programming in Nonlinear Model Identification

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

@InCollection{1793,
  author =       "Stephan M. Winkler and Michael Affenzeller and 
                 Stefan Wagner and Gabriel K. Kronberger and Michael Kommenda",
  title =        "Using Genetic Programming in Nonlinear Model
                 Identification",
  booktitle =    "Workshop on Identification in Automotive 2010",
  publisher =    "Springer",
  year =         "2010",
  editor =       "Daniel Alberer and Hakan Hjalmarsson and 
                 Luigi {del Re}",
  volume =       "418",
  series =       "Lecture Notes in Control and Information Sciences",
  chapter =      "6",
  pages =        "89--109",
  address =      "Linz, Austria",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4471-2221-0",
  URL =          "https://link.springer.com/chapter/10.1007/978-1-4471-2221-0_6",
  DOI =          "doi:10.1007/978-1-4471-2221-0_6",
  abstract =     "In this paper we summarize the use of genetic
                 programming (GP) in nonlinear system identification:
                 After giving a short introduction to evolutionary
                 computation and genetic algorithms, we describe the
                 basic principles of genetic programming and how it is
                 used for data based identification of nonlinear
                 mathematical models. Furthermore, we summarize projects
                 in which we have successfully applied GP in Research
                 and Development projects in the last years; we also
                 give a summary of several algorithmic enhancements that
                 have been successfully researched in the last years
                 (including offspring selection, on-line and sliding
                 window GP, operators for monitoring genetic process
                 dynamics, and the design of cooperative evolutionary
                 data mining agents). A short description of
                 HeuristicLab (HL), the optimization framework developed
                 by the HEAL research group, and the use of the GP
                 implementations in HL are given in the appendix of this
                 paper.",
  notes =        "Published 2012? LNCIS, volume 418",
}

Genetic Programming entries for Stephan M Winkler Michael Affenzeller Stefan Wagner Gabriel Kronberger Michael Kommenda

Citations