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Soft computing techniques in parameter identification and probabilistic seismic analysis of structures

Stavroulakis Georgios, Tsompanakis, Yiannis, Lagaros, Nikos D

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URIhttp://purl.tuc.gr/dl/dias/C1327DEB-7EA5-41C6-97EA-5AB71E895A57-
Identifierhttps://doi.org/10.1016/j.advengsoft.2007.06.004-
Languageen-
Extent12 pagesen
TitleSoft computing techniques in parameter identification and probabilistic seismic analysis of structuresen
CreatorStavroulakis Georgiosen
CreatorΣταυρουλακης Γεωργιοςel
CreatorTsompanakis, Yiannisen
CreatorLagaros, Nikos Den
PublisherElsevieren
Content SummaryThe objective of this paper is to investigate the efficiency of soft computing methods, in particular methodologies based on neural networks, when incorporated into the solution of computationally intensive engineering problems. Two types of applications have been considered, namely parameter (flaw) identification and probabilistic seismic analysis of structures. Artificial neural networks (ANNs) based metamodels are used in order to replace the time-consuming repeated structural analyses. The back-propagation algorithm is employed for training the ANN, using data derived from selected analyses. The trained ANN is then used to predict the values of the necessary data. The numerical tests demonstrate the computational advantages of the proposed methodologiesen
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-11-
Date of Publication2008-
SubjectEngineeringen
Bibliographic CitationY. Tsompanakis , N.D. Lagaros , G.E. Stavroulakis ,"Soft computing techniques in parameter identification and probabilistic seismic analysis of structures ,"Adv. in Eng. Software, vol. 39, no. 7, pp. 612–624, Ju.2008. doi:10.1016/j.advengsoft.2007.06.004en

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