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Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches

  • David Lehký
  • Ondřej Slowik
  • Drahomír Novák
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 436)

Abstract

The paper presents two alternative approaches to solve inverse reliability task – to determine the design parameters to achieve desired target reliabilities. The first approach is based on utilization of artificial neural networks and small-sample simulation Latin hypercube sampling. The second approach considers inverse reliability task as reliability-based optimization task using double-loop method and also small-sample simulation. Efficiency of both approaches is presented in numerical example, advantages and disadvantages are discussed.

Keywords

Inverse reliability artificial neural network reliability-based optimization double-loop optimization uncertainties Latin hypercube sampling 

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Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • David Lehký
    • 1
  • Ondřej Slowik
    • 1
  • Drahomír Novák
    • 1
  1. 1.Brno University of TechnologyBrnoCzech Republic

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