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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Energy (Oxford) Ročník 248; s. 123587
Hlavní autoři:	Fathy, Ahmed, Babu, Thanikanti Sudhakar, Abdelkareem, Mohammad Ali, Rezk, Hegazy, Yousri, Dalia
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.06.2022 Elsevier BV
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!