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Numerical simulation based on fuzzy stochastic analysis

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  • Bernd Möller
  • Wolfgang Graf
  • Jan-Uwe Sickert
  • Uwe Reuter

Abstract

In this paper mathematical methods for fuzzy stochastic analysis in engineering applications are presented. Fuzzy stochastic analysis maps uncertain input data in the form of fuzzy random variables onto fuzzy random result variables. The operator of the mapping can be any desired deterministic algorithm, e.g. the dynamic analysis of structures. Two different approaches for processing the fuzzy random input data are discussed. For these purposes two types of fuzzy probability distribution functions for describing fuzzy random variables are introduced. On the basis of these two types of fuzzy probability distribution functions two appropriate algorithms for fuzzy stochastic analysis are developed. Both algorithms are demonstrated and compared by way of an example.

Suggested Citation

  • Bernd Möller & Wolfgang Graf & Jan-Uwe Sickert & Uwe Reuter, 2007. "Numerical simulation based on fuzzy stochastic analysis," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 13(4), pages 349-364, August.
    • Handle: RePEc:taf:nmcmxx:v:13:y:2007:i:4:p:349-364
    DOI: 10.1080/13873950600994514
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    Cited by:

    1. Mahdi Montazerolghaem & Wolfram Jäger, 2016. "Fuzzy Numbers Applied in Reliability Assessment of Unreinforced Masonry Shear Wall," Modern Applied Science, Canadian Center of Science and Education, vol. 10(6), pages 147-147, June.

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