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Uncertainty Management in Rule Based Systems Application to Maneuvers Recognition

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

Abstract

In this paper we study the uncertainty management in expert systems. This task is very important especially when noised data are used such as in the CASSICE project, which will be presented later. Indeed, the use of a classical expert system in this case will generally produce mediocre results. We investigate the uncertainty management using the Dempster-Shafer theory of evidence and we discuss benefits and disadvantages of this approach by comparing the obtained results with those obtained by an expert system based on the fuzzy logic.

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Author information

Authors and Affiliations

  1. Université de Technologie de Troyes, 12 rue Marie Curie, BP 2060, 10010, Troyes Cedex, France

    T. Benouhiba & J. M. Nigro

Authors
  1. T. Benouhiba
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  2. J. M. Nigro
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Benouhiba, T., Nigro, J.M. (2003). Uncertainty Management in Rule Based Systems Application to Maneuvers Recognition. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_32

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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