Detail publikačního výsledku

Small-sample artificial neural network based response surface method for reliability analysis of concrete bridges

LEHKÝ, D.; ŠOMODÍKOVÁ, M.

Originální název

Small-sample artificial neural network based response surface method for reliability analysis of concrete bridges

Anglický název

Small-sample artificial neural network based response surface method for reliability analysis of concrete bridges

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

In the paper, an artificial neural network based response surface method (ANN-RSM) in combination with a small-sample simulation technique is proposed. ANN as powerful parallel computational system is used for approximation of limit state function (LSF). Thanks to its ability to generalize it is efficient to fit LSF even with small number of simulations compared to polynomial RSM. Efficiency is emphasized by utilization of stratified simulation for selection of ANN training set elements. Proposed method is tested using simple limit state function taken from literature as well as employed for reliability and load-bearing capacity assessment of concrete bridge within the framework of fully probabilistic analysis. Results are compared with those obtained by other reliability methods.

Anglický abstrakt

In the paper, an artificial neural network based response surface method (ANN-RSM) in combination with a small-sample simulation technique is proposed. ANN as powerful parallel computational system is used for approximation of limit state function (LSF). Thanks to its ability to generalize it is efficient to fit LSF even with small number of simulations compared to polynomial RSM. Efficiency is emphasized by utilization of stratified simulation for selection of ANN training set elements. Proposed method is tested using simple limit state function taken from literature as well as employed for reliability and load-bearing capacity assessment of concrete bridge within the framework of fully probabilistic analysis. Results are compared with those obtained by other reliability methods.

Klíčová slova

Artificial neural network, Response surface method, Probability of failure, Reliability index.

Klíčová slova v angličtině

Artificial neural network, Response surface method, Probability of failure, Reliability index.

Autoři

LEHKÝ, D.; ŠOMODÍKOVÁ, M.

Rok RIV

2016

Vydáno

01.01.2015

Nakladatel

Taylor & Francis Group

Místo

London, UK

ISBN

978-1-138-00120-6

Kniha

Proceedings of the Fourth International Symposium on Life-Cycle Civil Engineering (IALCCE 2014) – Life-Cycle of Structural Systems: Design, Assessment, Maintenance and Management

Strany od

1903

Strany do

1909

Strany počet

7

Plný text v Digitální knihovně

http://hdl.handle.net/

BibTex

@inproceedings{BUT112148,
  author="David {Lehký} and Martina {Sadílková Šomodíková}",
  title="Small-sample artificial neural network based response surface method for reliability analysis of concrete bridges",
  booktitle="Proceedings of the Fourth International Symposium on Life-Cycle Civil Engineering (IALCCE 2014) – Life-Cycle of Structural Systems: Design, Assessment, Maintenance and Management",
  year="2015",
  pages="1903--1909",
  publisher="Taylor & Francis Group",
  address="London, UK",
  isbn="978-1-138-00120-6"
}