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Emulating Process Simulators with Learning Systems

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Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005 (ICANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3697))

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Abstract

We explore the possibility of replacing a process simulator with a learning system. This is motivated in the presented test case setting by a need to speed up a simulator that is to be used in conjunction with an optimisation algorithm to find near optimal process parameters. Here we will discuss the potential problems and difficulties in this application, how to solve them and present the results from a paper mill test case.

An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .

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References

  1. Gillblad, D., et al.: Approximating process simulators with learning systems. SICS Technical Report T:2005:03, Swedish Institute of Computer Science (2004)

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  2. Rumelhart, D.E., McClelland, J.L.: Learning internal representations by error propagation. In: Parallel Distributed Processing, vol. I. MIT Press, Cambridge (1986)

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  3. Cover, T.: Estimation by The Nearest Neighbour rule. IEEE Transactions on Information Theory 14(1), 50–55 (1968)

    Article  MATH  Google Scholar 

  4. McLachlan, G., Peel, D.: Finite Mixture Models. Wiley & Sons, Chichester (2000)

    Book  MATH  Google Scholar 

  5. Good, I.J.: Probability and the Weighting of Evidence. Charles Griffin, London (1950)

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Author information

Authors and Affiliations

  1. Swedish Institute of Computer Science, Box 1263, SE-164 29, Kista, Sweden

    Daniel Gillblad, Anders Holst & Björn Levin

Authors
  1. Daniel Gillblad
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  2. Anders Holst
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  3. Björn Levin
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Editor information

Editors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015, HUT, Finland

    Erkki Oja

  4. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

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© 2005 Springer-Verlag Berlin Heidelberg

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Gillblad, D., Holst, A., Levin, B. (2005). Emulating Process Simulators with Learning Systems. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_60

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  • DOI: https://doi.org/10.1007/11550907_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28755-1

  • Online ISBN: 978-3-540-28756-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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