Generation of structured process models using genetic algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{pohlheim:1996:gspmuGA,
  author =       "Hartmut Pohlheim and Peter Marenbach",
  title =        "Generation of structured process models using genetic
                 algorithms",
  booktitle =    "Evolutionary Computing",
  publisher =    "Springer-Verlag",
  year =         "1996",
  editor =       "Terence C. Fogarty",
  number =       "1143",
  series =       "Lecture Notes in Computer Science",
  pages =        "102--109",
  address =      "University of Sussex, UK",
  month =        "1-2 " # apr,
  keywords =     "genetic algorithms, genetic programming, modelling,
                 SMOG, system identification, process models, structured
                 models, structure optimisation, parameter optimization,
                 control systems, learning control, industrial
                 application, biotechnology, Matlab, Smulink",
  ISBN =         "3-540-61749-3",
  URL =          "http://www.rtr.tu-darmstadt.de/fileadmin/literature/rst_96_26.pdf",
  DOI =          "doi:10.1007/BFb0032776",
  size =         "8 pages",
  abstract =     "The design of structured mathematical models of
                 processes in a certain level of abstraction defined by
                 the given task appears to be difficult and time
                 consuming even for experienced experts. This paper
                 reports on a new method for the design of structured
                 process models based on the metaphor of Genetic
                 Programming. This new methodology allows the automatic
                 generation of non-linear process models in a
                 self-organising way.",
  notes =        "The post-workshop proceedings of the 1996 AISB
                 workshop on evolutionary computing.

                 In this article describes further results taken form an
                 application of our approach on to artifical example
                 process which was designed and simulated using Matlab
                 and Simulink. from peter home page",
}

Genetic Programming entries for Hartmut Pohlheim Peter Marenbach

Citations