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LEHKÝ, D. SLOWIK, O. NOVÁK, D.
Original Title
Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches.
Type
conference paper
Language
English
Original 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.
Keywords
Inverse Reliability, artificial neural network, reliability-based optimization, double-loop optimization, uncertainties, Latin hypercube sampling
Authors
LEHKÝ, D.; SLOWIK, O.; NOVÁK, D.
RIV year
2014
Released
19. 9. 2014
Location
Řecko
ISBN
978-3-662-44653-9
Book
Proceedings of the 10th IFIP WG 12.5 International Conference Artificial Intelligence Applications and Inovations (AIAI 2014)
Pages from
344
Pages to
353
Pages count
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" }