X
Record #56553

Utilization of machine learning and neural networks to optimize the enclosure angle, magnetic field, and radiation parameter for mixed convection of hybrid nanofluid flow next to assess environmental impact

Publisher
Elsevier
Original paper date
Oct 30, 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, Duyun, Guizhou, 558000, China · Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, Shah Alam, Selangor, 40450, Malaysia · Mechanical Engineering Department, University of Technology, Baghdad, Iraq · Department of Industrial Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Alkharj, 16273, Saudi Arabia · Department of Electronics and Communication Engineering GLA University, Mathura, India · Department of Civil Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh, 11421, Saudi Arabia · Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Kurdistan Region, Iraq
Open access
No
Article type
Research Article
Broad categories
(B/T) Data Science(ENV) Environmental Sciences(PHY) Engineering - Chemical(PHY) Nanotechnology
Notes from Retraction Watch

see also: https://pubpeer.com/publications/65F4735C4A0D675A8A8AB69BE12F22

Citation lifecycle

How this paper is being cited

Pre-retraction
3
Same day
0
Post-retraction
5
% post-retraction
62.5%
~2.1 citations/yr before retraction · ~2.1 citations/yr after
— citing papers

Who is still citing this work

Loading…
Back to browse