Recent approach based heterogeneous comprehensive learning Archimedes optimization algorithm for identifying the optimal parameters of different fuel cells

A consistent and precise mathematical modeling play a vital role in the performance analysis of fuel cells (FCs) system. Model's efficiency completely depends on design accuracy. Thereby the modeling and estimation of FCs' parameters attracted numerous researchers. In this article, new inn...

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Veröffentlicht in:	Energy (Oxford) Jg. 248; S. 123587
Hauptverfasser:	Fathy, Ahmed, Babu, Thanikanti Sudhakar, Abdelkareem, Mohammad Ali, Rezk, Hegazy, Yousri, Dalia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.06.2022 Elsevier BV
Schlagworte:	Algorithms Archimedes optimization algorithm Comprehensive learning energy Fuel cells Fuel technology fuels Machine learning Mathematical models Model accuracy Optimization Optimization algorithms Parameter identification Parameters estimation Performance assessment Proton exchange membrane fuel cell Proton exchange membrane fuel cells Solid oxide fuel cell Solid oxide fuel cells Statistical analysis Steady state models Proton exchange membrane fuel cell Archimedes optimization algorithm Parameters estimation Comprehensive learning Solid oxide fuel cell
ISSN:	0360-5442, 1873-6785
Online-Zugang:	Volltext
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