Gu, X.; See, K.; Wang, Y.; Zhao, L.; Pu, W.
The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application. Energies 2021, 14, 3692.
https://doi.org/10.3390/en14123692
AMA Style
Gu X, See K, Wang Y, Zhao L, Pu W.
The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application. Energies. 2021; 14(12):3692.
https://doi.org/10.3390/en14123692
Chicago/Turabian Style
Gu, Xinyu, KW See, Yunpeng Wang, Liang Zhao, and Wenwen Pu.
2021. "The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application" Energies 14, no. 12: 3692.
https://doi.org/10.3390/en14123692
APA Style
Gu, X., See, K., Wang, Y., Zhao, L., & Pu, W.
(2021). The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application. Energies, 14(12), 3692.
https://doi.org/10.3390/en14123692
