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Reliability Analysis of Structures by Neural Network Supported Monte Carlo Methods

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Neural Networks and Soft Computing

Part of the book series: Advances in Soft Computing ((AINSC,volume 19))

Abstract

A forward neural network is used for generating samples in the Monte Carlo Methods. The patterns for network training and testing are computed by a FE program. A high numerical efficiency of the proposed approach is demonstrated on example of a plane multistorey elastoplastic frame.

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References

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Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Zielona Góra, ul. Prof. Z. Szafrana 2, 65-516, Zielona Góra, Poland

    Joanna Kaliszuk

  2. Institute of computer Methods in Civil Engineering, Cracow University of Technology, ul. Warszawska 24, 31-155, Kraków, Poland

    Zenon Waszczyszyn

Authors
  1. Joanna Kaliszuk
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  2. Zenon Waszczyszyn
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Technical University Częstochowa, Al. Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski

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

    Janusz Kacprzyk

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© 2003 Springer-Verlag Berlin Heidelberg

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Kaliszuk, J., Waszczyszyn, Z. (2003). Reliability Analysis of Structures by Neural Network Supported Monte Carlo Methods. In: Rutkowski, L., Kacprzyk, J. (eds) Neural Networks and Soft Computing. Advances in Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1902-1_117

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  • DOI: https://doi.org/10.1007/978-3-7908-1902-1_117

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0005-0

  • Online ISBN: 978-3-7908-1902-1

  • eBook Packages: Springer Book Archive

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