Publication detail

Reliability-based design optimization using artificial neural network inverse analysis

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

6

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"
}