Přístupnostní navigace
E-application
Search Search Close
Publication result detail
SLOWIK, O.; LEHKÝ, D.; NOVÁK, D.
Original Title
Reliability-based design optimization using artificial neural network inverse analysis
English Title
Type
Paper in proceedings outside WoS and Scopus
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.
English abstract
Keywords
Reliability-based, optimization, neural network, inverse analysis
Key words in English
Authors
RIV year
2019
Released
12.09.2018
Book
16th International Probabilistic Workshop
ISBN
1437-1006
Periodical
Beton- und Stahlbetonbau
Volume
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="0005-9900", url="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf" }