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PAN, L. NOVÁK, D. NOVÁK, L.
Originální název
Surrogate modelling of concrete girders using artificial neural network ensemble
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Surrogate model as approximation model is widely applied in engineering application, perform-ing sufficient amount of simulations for a fully probabilistic design of computationally demanding tasks. There are several types of new surrogate modelling techniques in last decades. Herein, artificial neural network en-semble (ANNE) is employed for surrogate modelling, which is very efficient method as will be shown on analytical example. Moreover, a comparison of traditional single artificial neural network approach and ANNE will be presented as well. Main part of the paper will be focused on application of ANNE for stochastic analysis of concrete girders represented by mathematical model in form of nonlinear finite element model. Therefore, in the last part of the paper, results obtained by ANNE will be presented and discussed.
Klíčová slova
Artificial Neural Network, Surrogate modeling, probabilistic design
Autoři
PAN, L.; NOVÁK, D.; NOVÁK, L.
Vydáno
15. 12. 2020
Místo
Shanghai, China
ISBN
9780429343292
Kniha
Life-Cycle Civil Engineering: Innovation, Theory and Practice. Proceedings of the 7th International Symposium on Life-Cycle Civil Engineering (IALCCE 2020), October 27-30, 2020, Shanghai, China
Strany od
1
Strany do
5
Strany počet
BibTex
@inproceedings{BUT169150, author="Lixia {Pan} and Drahomír {Novák} and Lukáš {Novák}", title="Surrogate modelling of concrete girders using artificial neural network ensemble", booktitle="Life-Cycle Civil Engineering: Innovation, Theory and Practice. Proceedings of the 7th International Symposium on Life-Cycle Civil Engineering (IALCCE 2020), October 27-30, 2020, Shanghai, China", year="2020", pages="1--5", address="Shanghai, China", doi="10.1201/9780429343292-162", isbn="9780429343292" }