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Advances in Lithium-Ion Battery SOC Prediction: A Data-Driv..:
, In:
2023 11th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)
,
Hassan, Al Amir
;
Yahia, Abdallah
;
Tamer, Moayadeldin
... - p. 253-258 , 2023
Link:
https://doi.org/10.1109/JAC-ECC61002.2023.10479643
RT T1
2023 11th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)
: T1
Advances in Lithium-Ion Battery SOC Prediction: A Data-Driven GRU-RNN Framework
UL https://suche.suub.uni-bremen.de/peid=ieee-10479643&Exemplar=1&LAN=DE A1 Hassan, Al Amir A1 Yahia, Abdallah A1 Tamer, Moayadeldin A1 Shahin, Mohamed A1 Zewail, Rami A1 Abdel-Rahim, Omar YR 2023 K1 Lithium-ion batteries K1 Temperature distribution K1 Recurrent neural networks K1 Battery management systems K1 Transportation K1 Real-time systems K1 Safety K1 State of Charge (SOC) K1 Mean Absolute Error K1 Gated Recurrent Unit (GRU) K1 Recurrent Neural Network SP 253 OP 258 LK http://dx.doi.org/https://doi.org/10.1109/JAC-ECC61002.2023.10479643 DO https://doi.org/10.1109/JAC-ECC61002.2023.10479643 SF ELIB - SuUB Bremen
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