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1
Modelling Data-Driven Digital Twins of EV Batteries for Pre..:
, In:
2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)
,
Fouka, Afroditi
;
Lepenioti, Katerina
;
Bousdekis, Alexandros
. - p. 1-8 , 2023
Link:
https://doi.org/10.1109/IISA59645.2023.10345850
RT T1 <cTitle>2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)</cTitle>: T1 <Title>Modelling Data-Driven Digital Twins of EV Batteries for Predictive Analytics</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10345850&Exemplar=1&LAN=DE A1 Fouka, Afroditi A1 Lepenioti, Katerina A1 Bousdekis, Alexandros A1 Mentzas, Gregoris YR 2023 K1 Lithium-ion batteries K1 Analytical models K1 Systematics K1 Fuses K1 Predictive models K1 Prediction algorithms K1 Electric vehicles K1 digital twin K1 Li-ion battery K1 electric vehicle K1 RAMI 4.0 K1 data analytics K1 machine learning SP 1 OP 8 LK http://dx.doi.org/https://doi.org/10.1109/IISA59645.2023.10345850 DO https://doi.org/10.1109/IISA59645.2023.10345850 SF ELIB - SuUB Bremen
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