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Generation of structured process models using Genetic Programming

  • Hartmut Pohlheim
  • Peter Marenbach
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1143)

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-organizing way.

Keywords

genetic programming modelling system identification process models structured models structure optimization parameter optimization control systems learning control industrial application biotechnology SMOG Matlab Smulink 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Hartmut Pohlheim
    • 1
  • Peter Marenbach
    • 2
  1. 1.Systems Technology ResearchDaimler Benz AGBerlin
  2. 2.Institute of Control Engineering Department of Systems Theory & RoboticsDarmstadt University of TechnologyDarmstadt

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