Prediction and optimization of sustainable fuel cells behavior using artificial intelligence algorithms

Zaferani, Seyed Peiman Ghorbanzade; Amiri, Mahmoud Kiannejad; Emami, M. Reza; Zahmatkesh, Sasan; Hajiaghaei–Keshteli, Mostafa; Panchal, Hitesh

doi:10.1016/j.ijhydene.2023.03.335

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Prediction and optimization of sustainable fuel cells behavior using artificial intelligence algorithms

Cited by 11 publications

References 22 publications

Overview: Fuel Cells, Hydrogen Energy, Science, Materials, Nanotechnology, Artificial Intelligence and State of the Art

Overview: Fuel Cells, Hydrogen Energy, Science, Materials, Nanotechnology, Artificial Intelligence and State of the Art

WITHDRAWN: Effects of hydraulic retention time and cultivation on nutrients removal and biomass production in wastewater by membrane photobioreactor: modeling and optimization by machine learning and response surface methodology

An event-triggered and dimension learning scheme WOA for PEMFC modeling and parameter identification

Contact Info

Product

Resources

About