Physics-informed neural network for long-term prognostics of proton exchange membrane fuel cells
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Abstract
No abstract available for this paper.
Citation impact
50
total citations
- FWCI
- 28.67
- Percentile
- 100%
- References
- 62
Citations per year
Authors
4- TKTaehwan Ko
Anyang University
- DKDukyong Kim
Anyang University
- JPJaewoong Park
Anyang University
- SHSeung Hwan LeeCorresponding
Anyang University
Topics & keywords
Topics
Keywords
- Prognostics
- Term (time)
- Proton exchange membrane fuel cell
- Artificial neural network
- Fuel cells
- Nuclear engineering
- Engineering
- Physics
UN Sustainable Development Goals
- Affordable and clean energy
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