Detail publikace

Reliability-based design optimization using artificial neural network inverse analysis

SLOWIK, O. LEHKÝ, D. NOVÁK, D.

Originální název

Reliability-based design optimization using artificial neural network inverse analysis

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Reliability-based, optimization, neural network, inverse analysis

Autoři

SLOWIK, O.; LEHKÝ, D.; NOVÁK, D.

Vydáno

12. 9. 2018

ISSN

1437-1006

Periodikum

Beton- und Stahlbetonbau

Ročník

113

Číslo

S2

Stát

Spolková republika Německo

Strany od

1

Strany do

6

Strany počet

6

URL

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"
}