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A performance prediction method based on data-driven for proton exchange membrane electrolyzer: deep learning and optimization
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DOI：10.1016/j.ijhydene.2026.154726.png)
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摘要
En 中文
• 提出了一种基于神经网络的集成数值模型用于优先级排序。
• 该数据驱动方法的决定系数为0.9967。
• 温度均匀性可提高46.69%。
Keyword:
data-driven method
proton exchange membrane electrolyzer
deep learning
performance prediction
optimization
期刊
IF:
8.3
论文数:
5.5W
被引数:
23.1W
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