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PAN, L.; LEHKÝ, D.; NOVÁK, D.; SLOWIK, O.
Original Title
Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.
English Title
Type
Paper in proceedings outside WoS and Scopus
Original Abstract
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.
English abstract
Keywords
Sensitivity analysis, prestressed concrete girders, neural network
Key words in English
Authors
RIV year
2019
Released
12.09.2018
Book
16th International Probabilistic Workshop
ISBN
1437-1006
Periodical
Beton- und Stahlbetonbau
Volume
113
Number
S2
State
Federal Republic of Germany
Pages from
1
Pages to
5
Pages count
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="0005-9900", url="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbest.201800059&file=best201800059-sup-0001-suppinfo.pdf" }