Neural-fuzzy machine learning approach for the fatigue-creep reliability modeling of SAC305 solder joints
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 1 online resource.
- Sprache
-
Englisch
- Erschienen in
-
Neural-fuzzy machine learning approach for the fatigue-creep reliability modeling of SAC305 solder joints ; volume:13 ; number:1 ; day:26 ; month:5 ; year:2023 ; pages:1-19 ; date:12.2023
Scientific reports ; 13, Heft 1 (26.5.2023), 1-19, 12.2023
- Klassifikation
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Ingenieurwissenschaften und Maschinenbau
- Urheber
-
Bani Hani, Dania
Al Athamneh, Raed
Abueed, Mohammed
Hamasha, Sa’d
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-023-32460-4
- URN
-
urn:nbn:de:101:1-2023091108274469682672
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:51 MESZ
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Beteiligte
- Bani Hani, Dania
- Al Athamneh, Raed
- Abueed, Mohammed
- Hamasha, Sa’d
- SpringerLink (Online service)
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