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Using Imprecise and Uncertain Information to Enhance the Diagnosis of a Railway Device

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Nonlinear Mathematics for Uncertainty and its Applications

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 100))

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Abstract

This paper investigates the use of partially reliable information elicited from multiple experts to improve the diagnosis of a railway infrastructure device. The general statistical model used to perform the diagnosis task is based on a noiseless Independent Factor Analysis handled in a soft-supervised learning framework.

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Author information

Authors and Affiliations

  1. UPE, IFSTTAR, GRETTIA, 2 rue de la Butte Verte, 93166, Noisy-le-Grand, France

    Zohra L. Cherfi, Etienne Côme & Patrice Aknin

  2. LISSI, UPE Créteil, 61 av du Gal de Gaulle, 94100, Créteil, France

    Latifa Oukhellou

  3. HEUDIASYC, UTC, UMR CNRS 6599, B.P 20529, 60205, Compiégne, France

    Thierry Denœux

Authors
  1. Zohra L. Cherfi
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  2. Latifa Oukhellou
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  3. Etienne Côme
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  4. Thierry Denœux
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  5. Patrice Aknin
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Editor information

Editors and Affiliations

  1. College of Applied Sciences, Beijing University of Technology, 100 Pingleyuan, 100124, Chaoyang District, Beijing, P.R. China

    Shoumei Li , Xia Wang  & Li Guan ,  & 

  2. Department of Systems Design and Informatics, Kyushu Institute of Technology, 680-4, Kawazu, 820-8502, lizuka, Japan

    Yoshiaki Okazaki

  3. Department of Mathematics, Shinshu University, 4-17-1 Wakasato, 380-8553, Nagano, Japan

    Jun Kawabe

  4. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259-G3-47, Nagatsuta, Midori-ku, 226-8502, Yokohama, Japan

    Toshiaki Murofushi

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© 2011 Springer-Verlag Berlin Heidelberg

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Cherfi, Z.L., Oukhellou, L., Côme, E., Denœux, T., Aknin, P. (2011). Using Imprecise and Uncertain Information to Enhance the Diagnosis of a Railway Device. In: Li, S., Wang, X., Okazaki, Y., Kawabe, J., Murofushi, T., Guan, L. (eds) Nonlinear Mathematics for Uncertainty and its Applications. Advances in Intelligent and Soft Computing, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22833-9_25

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  • DOI: https://doi.org/10.1007/978-3-642-22833-9_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22832-2

  • Online ISBN: 978-3-642-22833-9

  • eBook Packages: EngineeringEngineering (R0)

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