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A Novel Deep Belief Network and Extreme Learning Machine Based Performance Degradation Prediction Method for Proton Exchange Membrane Fuel Cell

机译：一种新的深度信念网络和基于极端学习机的质子交换膜燃料电池的性能降解预测方法

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Yucen Xie; Jianxiao Zou; Zhongliang Li; Fei Gao; Chao Peng;
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1. Performance prediction and power density maximization of a proton exchange membrane fuel cell based on deep belief network [J] . Li Hong-Wei, Xu Bo-Shi, Du Chang-He, Journal of power sources . 2020,第Juna15期

机译：基于深度信仰网络的质子交换膜燃料电池的性能预测和功率密度最大化
2. Nonlinear Performance Degradation Prediction of Proton Exchange Membrane Fuel Cells Using Relevance Vector Machine [J] . Yiming Wu, Elena Breaz, Fei Gao, IEEE Transactions on Energy Conversion . 2016,第4期

机译：关联向量机预测质子交换膜燃料电池的非线性性能退化
3. Online voltage consistency prediction of proton exchange membrane fuel cells using a machine learning method [J] . Chen Huicui, Shan Wanchao, Liao Hongyang, International journal of hydrogen energy . 2021,第69期

机译：使用机器学习方法的质子交换膜燃料电池在线电压一致性预测
4. Remaining useful life estimation for proton exchange membrane fuel cell based on extreme learning machine [C] . Xiaoling Xue, Yanyan Hu, Shuai Qi Youth Academic Annual Conference of Chinese Association of Automation . 2016

机译：基于极限学习机的质子交换膜燃料电池剩余使用寿命估算
5. Nanofiber network composite membranes for proton exchange membrane fuel cells. [D] . Choi, Jonghyun. 2010

机译：用于质子交换膜燃料电池的纳米纤维网络复合膜。
6. Use of a Sparse-Response Deep Belief Network and Extreme Learning Machine to Discriminate Alzheimers Disease Mild Cognitive Impairment and Normal Controls Based on Amyloid PET/MRI Images [O] . Ping Zhou, Shuqing Jiang, Lun Yu, 2020

机译：利用稀疏响应的深度信仰网络和极端学习机鉴别阿尔茨海默病轻度认知障碍和基于淀粉样宠/ MRI图像的正常对照
7. Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems . [O] . Silva R.E., Gouriveau Rafael, Jemei Samir, 2014

机译：基于自适应神经模糊推理系统的质子交换膜燃料电池退化预测。

A Novel Deep Belief Network and Extreme Learning Machine Based Performance Degradation Prediction Method for Proton Exchange Membrane Fuel Cell

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