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Detail publikačního výsledku
LEHKÝ, D.; NOVÁK, D.
Originální název
Inverse reliability problem solved by artificial neural networks
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
An efficient inverse reliability analysis method is proposed to obtain design parameters in order to achieve the prescribed reliability level. The inverse analysis method is based on the coupling of an artificial neural network and a small-sample simulation method of the Monte Carlo type used for efficient stochastic preparation of the training set utilized in artificial neural network training. The calculation of reliability is performed using the first order reliability method. The validity and efficiency of the approach is shown using numerical examples taken from the literature as well as from civil engineering computational mechanics for both single and multiple design parameters and single and multiple reliability constraints.
Anglický abstrakt
Klíčová slova
Design parameters; First order reliability methods; Inverse analysis methods; Inverse reliability analysis; Inverse reliability problem; Multiple reliability constraints; Reliability level; Training sets
Klíčová slova v angličtině
Autoři
Vydáno
16.06.2013
Místo
New York, USA
ISBN
978-1-138-00086-5
Kniha
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures
Strany od
5303
Strany do
5310
Strany počet
8
BibTex
@inproceedings{BUT107532, author="David {Lehký} and Drahomír {Novák}", title="Inverse reliability problem solved by artificial neural networks", booktitle="Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures", year="2013", pages="5303--5310", address="New York, USA", isbn="978-1-138-00086-5" }