Utilizing advanced machine learning approaches to assess the seismic fragility of non-engineered masonry structures
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: Results in engineering(21), S.1-15 - ISSN 2590-1230
In: Elsevier BV, Amsterdam
- Schlagwort
-
Maschinelles Lernen
- Ereignis
-
Veröffentlichung
- (wo)
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Weimar
- (wer)
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Bauhaus-Universität Weimar
- (wann)
-
2024
- Urheber
- URN
-
urn:nbn:de:gbv:wim2-20240229-162927-007
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:21 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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Beteiligte
- Harirchian, Ehsan
- Aghakouchaki Hosseini, Seyed Ehsan
- Novelli, Viviana
- Lahmer, Tom
- Rasulzade, Shahla
- Bauhaus-Universität Weimar
Entstanden
- 2024
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