fig7

A critical review of the machine learning guided design of metallic glasses for superior glass-forming ability

Figure 7. Comparison of GFA predictions from (A) RQGPR and (B) LMANN models with the experimental results obtained from the quasi-ternary Zr-Cu-(Ag, Al) system by Inoue et al.[52]. Reprinted from Ref.[31], copyright (2021), with permission from Springer Nature. GFA: Glass-forming ability; RQGPR: ration quadratic kernel-based Gaussian process regression; LMANN: Levenberg-Marquardt backpropagation artificial neural network.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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