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SLOWIK, O. LEHKÝ, D. NOVÁK, D.
Original Title
Reliability-based design optimization using artificial neural network inverse analysis
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
An efficient approach to reliability-based design optimization is presented. It is aimed for solving inverse reliability problems with multiple solutions of optimal design parameters with respect to the target reliability constraints. The main goal is to propose procedure which can employ artificial neural network surrogate model in order to obtain set of design parameters securing defined level of reliability. Objective function can be defined as simple function of dependent and independent variables, e.g. cost of the structure calculated based on the volume and type of materials used.
Keywords
Reliability-based, optimization, neural network, inverse analysis
Authors
SLOWIK, O.; LEHKÝ, D.; NOVÁK, D.
Released
12. 9. 2018
ISBN
1437-1006
Periodical
Beton- und Stahlbetonbau
Year of study
113
Number
S2
State
Federal Republic of Germany
Pages from
1
Pages to
6
Pages count
URL
https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf
BibTex
@inproceedings{BUT156407, author="Ondřej {Slowik} and David {Lehký} and Drahomír {Novák}", title="Reliability-based design optimization using artificial neural network inverse analysis", booktitle="16th International Probabilistic Workshop", year="2018", journal="Beton- und Stahlbetonbau", volume="113", number="S2", pages="1--6", issn="1437-1006", url="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf" }