Detail publikace
Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches.
LEHKÝ, D. SLOWIK, O. NOVÁK, D.
Originální název
Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches.
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Inverse Reliability, artificial neural network, reliability-based optimization, double-loop optimization, uncertainties, Latin hypercube sampling
Autoři
LEHKÝ, D.; SLOWIK, O.; NOVÁK, D.
Rok RIV
2014
Vydáno
19. 9. 2014
Místo
Řecko
ISBN
978-3-662-44653-9
Kniha
Proceedings of the 10th IFIP WG 12.5 International Conference Artificial Intelligence Applications and Inovations (AIAI 2014)
Strany od
344
Strany do
353
Strany počet
10
BibTex
@inproceedings{BUT112900,
author="David {Lehký} and Ondřej {Slowik} and Drahomír {Novák}",
title="Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches.",
booktitle="Proceedings of the 10th IFIP WG 12.5 International Conference Artificial Intelligence Applications and Inovations (AIAI 2014)",
year="2014",
pages="344--353",
address="Řecko",
isbn="978-3-662-44653-9"
}