机译:生成对抗网络-CLS与双向短期内存相结合的锂离子电池状态预测
Univ Oklahoma Norman OK 73019 USA;
Shaanxi Univ Sci & Technol Coll Elect & Informat Engn Xian 710021 Shaanxi Peoples R China;
Calif State Univ Fresno Dept Elect & Comp Engn Fresno CA 93740 USA;
Chungnam Natl Univ Energy Storage & Convers Lab Dept Elect Engn Daejeon 34134 South Korea;
Chungnam Natl Univ Energy Storage & Convers Lab Dept Elect Engn Daejeon 34134 South Korea;
Battery state prediction; Generative adversarial network-CLS; Bidirectional-long short-term memory; Recurrent neural network; State-of-charge;
机译:基于长时记忆和Elman神经网络混合模型的锂离子电池剩余使用寿命预测
机译:用于锂离子电池荷电状态估计的堆叠式双向长短期存储网络
机译:基于双向长短期记忆编码器-解码器架构的锂离子电池充电状态序列估计
机译:利用新型长短期记忆网络剩余锂离子电池的早期预测
机译:双向长期内存网络,用于原型对象表示
机译:基于双向短期内存和卷积神经网络组合的温度预测与数值预测数据相结合
机译:基于双向短期内存和卷积神经网络组合的温度预测,与数值预测数据相结合