Optimization and design of machine learning computational technique for prediction of physical separation process

• Main Authors: Haiqing Li, Chairun Nasirin, Azher M. Abed, Dmitry Olegovich Bokov, Lakshmi Thangavelu, Haydar Abdulameer Marhoon, Md Lutfor Rahman
• Format: Article
• Language: English; English
• Published: Elsevier B.V 2022
• Subjects: T57.6-57.97 Operations research. Systems analysis
• Online Access: https://eprints.ums.edu.my/id/eprint/32773/1/Optimization%20and%20design%20of%20machine%20learning%20computational%20technique%20for%20prediction%20of%20physical%20separation%20process.ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32773/2/Optimization%20and%20design%20of%20machine%20learning%20computational%20technique%20for%20prediction%20of%20physical%20separation%20process.pdf; https://eprints.ums.edu.my/id/eprint/32773/; https://www.sciencedirect.com/science/article/pii/S187853522100695X; https://doi.org/10.1016/j.arabjc.2021.103680

Machine learning (ML) methods were developed and optimized for description and understanding a physical separation process. Indeed, this work indicates application of machine learning technique for a real physical system and optimization of process parameters to achieve the target. A bunch of datase...