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Record #72408

Deep-learning optimization and environmental assessment of nanomaterial's boosted hydrogen and power generation system combined with SOFC

Publisher
Elsevier
Original paper date
Dec 22, 2022
Institution
School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, Guizhou, 558000, China · Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun, Guizhou, 558000, China · Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia · Department of Management Information Systems, College of Business Administration - Hawtat Bani Tamim, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia · Department of Computer Sciences, Faculty of Computing and Information Technology -Al-Turbah, Taiz University, Taiz 9674, Yemen · Mechanical Engineering Department, University of Technology, Baghdad, Iraq · Department of Civil Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia · Department of Civil Engineering, College of Engineering, Cihan University-Erbil, Erbil, Iraq · Department of Mechanical Engineering, Institute of Engineering and Technology, GLA University, Mathura (U.P), 281406, India
Open access
No
Article type
Research Article
Broad categories
(B/T) Computer Science(ENV) Environmental Sciences(PHY) Engineering - Chemical(PHY) Engineering - Electrical(PHY) Nanotechnology
Citation lifecycle

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Pre-retraction
4
Same day
0
Post-retraction
0
% post-retraction
0.0%
~1.1 citations/yr before retraction
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