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Knowledge Management in Process Modelling

Study of Expert Systems for Supervisory Control
  • R. V. van de Ree
  • H. Koppelaar
  • E. J. H. Kerckhoffs
Chapter
Part of the Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 9)

Abstract

Models of (chemical) plants tend to be very large. They will also contain knowledge from various sources. To manage these models we need special techniques or tools. In this paper we present three basic ideas to control model complexity:
  1. 1.

    hierarchical structures with knowledge abstraction

     
  2. 2.

    knowledge integration

     
  3. 3.

    efficient data propagation

     

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References

  1. [1]
    Kleene, S.C., ‘Representation of Events in Nerve Nets and Finite Automata’ in C.E. Shannon and M. McCarthy (eds.), Automata Studies, Annals of Math. Studies, no. 34, Princeton, New York, 1956, pp.3–41.Google Scholar
  2. [2]
    Kuipers, B. ‘Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge’ in Automatica, Vol.25, No.4, pp. 571–585, 1989Google Scholar
  3. [3]
    Leler, Wm., ‘Constraint Programming Languages, Their Specification and Generation’ Addison-Wesley, Amsterdam, 1988, ISBN 0–201–06243–7Google Scholar
  4. [4]
    Ree, R.V. van de, Koppelaar, H., and Kerckhoffs, E.J.H., ‘Proposal for Process Modelling’ in Proceedings IMACS MCTS 91 Modelling and Control of Technological Systems, GERFIDN, France, 1991, ISBN 29502908–1–7Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1991

Authors and Affiliations

  • R. V. van de Ree
    • 1
  • H. Koppelaar
    • 1
  • E. J. H. Kerckhoffs
    • 1
  1. 1.Delft University of TechnologyNetherlands

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