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Soft Methods for Integrated Uncertainty Modelling pp 103–110Cite as

A Method to Simulate Fuzzy Random Variables

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Part of the book series: Advances in Soft Computing ((AINSC,volume 37))

Abstract

In this paper a method is introduced to simulate fuzzy random variables by using the support function. On the basis of the support function, the class of values of a fuzzy random variable can be ‘identified’ with a closed convex cone of a Hilbert space, and we now suggest to simulate Hilbert space-valued random elements and to project later into such a cone. To make easier the projection above we will consider isotonic regression. The procedure will be illustrated by means of several examples.

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Author information

Authors and Affiliations

  1. Dpto. de Estadística e I.O., Universidad de Oviedo, 33007, Spain

    González-Rodríguez G. & Coppi R.

Authors
  1. González-Rodríguez G.
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  2. Colubi A.
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  3. Gil M.A.
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  4. Coppi R.
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Editor information

Editors and Affiliations

  1. AI Group Department of Engineering Mathematics, University of Bristol, BS8 1TR, Bristol, UK

    Jonathan Lawry

  2. Statistics and Operations Research, Rey Juan Carlos University, C-Tulip˙n s/n MÛstoles28933, Spain

    Enrique Miranda

  3. Intelligent Systems Group Department of Electronics & Computer Science, University of Santiago de Compostela Santiago de Compostela, Spain

    Alberto Bugarin

  4. Department of Applied Mathematics, Beijing University of Technology, 100022, Beijing, P.R. China

    Shoumei Li

  5. Dpto. Estadistica e I.O y D.M. Calle Calvo Sotelo s/n, Universiad de Oviedo Fac. Ciencias, 33071, Oviedo, Spain

    Maria Angeles Gil

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

    Przemys aw Grzegorzewski

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

    Olgierd Hyrniewicz

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© 2006 Springer

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G., GR., A., C., M.A., G., R., C. (2006). A Method to Simulate Fuzzy Random Variables. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_14

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  • DOI: https://doi.org/10.1007/3-540-34777-1_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34776-7

  • Online ISBN: 978-3-540-34777-4

  • eBook Packages: EngineeringEngineering (R0)

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