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Review on machine learning techniques for the assessment of..:
Centola, Alessio
;
Tridello, Andrea
;
Ciampaglia, Alberto
..
Fatigue & Fracture of Engineering Materials & Structures. 47 (2024) 8 - p. 2700-2729 , 2024
Link:
https://doi.org/10.1111/ffe.14326
RT Journal T1 <Title>Review on machine learning techniques for the assessment of the fatigue response of additively manufactured metal parts</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1111_ffe.14326&Exemplar=1&LAN=DE A1 Centola, Alessio A1 Tridello, Andrea A1 Ciampaglia, Alberto A1 Berto, Filippo A1 Paolino, Davide Salvatore PB Wiley YR 2024 SN 8756-758X SN 1460-2695 JF Fatigue & Fracture of Engineering Materials & Structures VO 47 IS 8 SP 2700 OP 2729 LK http://dx.doi.org/https://doi.org/10.1111/ffe.14326 DO https://doi.org/10.1111/ffe.14326 SF ELIB - SuUB Bremen
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