An active machine learning approach for optimal design of magnesium alloys using Bayesian optimisation.

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作者： M,Ghorbani ^[1] ; M,Boley ^[2] ; P N H,Nakashima ^[3] ; N,Birbilis ^[4]

作者单位： Department of Materials Science and Engineering, Monash University, Melbourne, VIC, 3800, Australia. marzie.ghorbani@deakin.edu.au. ^[1] Faculty of Engineering, Science and the Built Environment, Deakin University, Waurn Ponds, VIC, 3125, Australia. marzie.ghorbani@deakin.edu.au. ^[2] Faculty of Information Technology, Monash University, Melbourne, VIC, 3800, Australia. ^[3] Department of Materials Science and Engineering, Monash University, Melbourne, VIC, 3800, Australia. ^[4] Faculty of Engineering, Science and the Built Environment, Deakin University, Waurn Ponds, VIC, 3125, Australia. nick.birbilis@deakin.edu.au. ^[5]

关键词 Alloy design Bayesian optimisation Machine learning Mg alloys Sequential design strategy

DOI 10.1038/s41598-024-59100-9

PMID 38594488

发布时间 2024-04-11

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