Optimal estimation of the PEM fuel cells applying deep belief network optimized by improved archimedes optimization algorithm

The present study proposes a new efficient methodology for optimal model identification of the Proton-exchange membrane fuel cell (PEMFC) stacks based on an improved version of a Deep Belief Network (DBN). The proposed DBN has been updated by a new metaheuristic to provide the minimum relative error...

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Veröffentlicht in:	Energy (Oxford) Jg. 237; S. 121532
Hauptverfasser:	Sun, Xianke, Wang, Gaoliang, Xu, Liuyang, Yuan, Honglei, Yousefi, Nasser
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 15.12.2021 Elsevier BV
Schlagworte:	Algorithms Belief networks Deep belief network electric potential difference Fuel cells Fuel technology Heuristic methods Improved archimedes optimization algorithm Model estimation Optimization Optimization algorithms Output voltage Proton exchange membrane fuel cells Protons Stacks Model estimation Proton-exchange membrane fuel cells Deep belief network Improved archimedes optimization algorithm Output voltage
ISSN:	0360-5442, 1873-6785
Online-Zugang:	Volltext
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