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1 Ergebnisse
1
Modeling Power-Bus Structures with Physics-Informed Neural ..:
, In:
2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal & Power Integrity: EMC Japan / Asia-Pacific International Symposium on Electromagnetic Compatibility (EMC Japan/APEMC Okinawa)
,
Fujita, Kazuhiro
- p. 552-555 , 2024
Link:
https://doi.org/10.23919/EMCJapan/APEMCOkinaw58965.202..
RT T1 <cTitle>2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal & Power Integrity: EMC Japan / Asia-Pacific International Symposium on Electromagnetic Compatibility (EMC Japan/APEMC Okinawa)</cTitle>: T1 <Title>Modeling Power-Bus Structures with Physics-Informed Neural Networks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10584946&Exemplar=1&LAN=DE A1 Fujita, Kazuhiro YR 2024 SN 2640-7469 K1 Dielectric losses K1 Artificial neural networks K1 Voltage K1 Electromagnetic modeling K1 Electromagnetic compatibility K1 Conductors K1 Mathematical models K1 deep learning K1 artificial neural network K1 power-bus structure K1 partial differential equation K1 electromagnetic field SP 552 OP 555 LK http://dx.doi.org/https://doi.org/10.23919/EMCJapan/APEMCOkinaw58965.2024.10584946 DO https://doi.org/10.23919/EMCJapan/APEMCOkinaw58965.2024.10584946 SF ELIB - SuUB Bremen
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