Detail publikace

Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.

PAN, L. LEHKÝ, D. NOVÁK, D. SLOWIK, O.

Originální název

Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

The paper describes a neural network ensemble-based parameter sensitivity analysis, which is compared with selected sensitivity analysis techniques usually utilized in stochastic structural modeling. The accuracy, stability and efficiency of the mentioned sensitivity analysis techniques are compared on example of prestressed concrete girder.

Klíčová slova

Sensitivity analysis, prestressed concrete girders, neural network

Autoři

PAN, L.; LEHKÝ, D.; NOVÁK, D.; SLOWIK, O.

Vydáno

12. 9. 2018

ISSN

1437-1006

Periodikum

Beton- und Stahlbetonbau

Ročník

113

Číslo

S2

Stát

Spolková republika Německo

Strany od

1

Strany do

5

Strany počet

5

URL

https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf

BibTex

@inproceedings{BUT156408,
  author="Lixia {Pan} and David {Lehký} and Drahomír {Novák} and Ondřej {Slowik}",
  title="Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.",
  booktitle="16th International Probabilistic Workshop",
  year="2018",
  journal="Beton- und Stahlbetonbau",
  volume="113",
  number="S2",
  pages="1--5",
  issn="1437-1006",
  url="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf"
}