Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation
Bayesian optimisation (BO) protocols grounded in active learning (AL) principles have gained significant recognition for their ability to efficiently optimize black-box objective functions. This capability is critical for advancing autonomous and high-throughput materials design and discovery proces...
Saved in:
Main Authors: | Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
|
Series: | Machine Learning: Science and Technology |
Subjects: | |
Online Access: | https://doi.org/10.1088/2632-2153/ada47d |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing the performance of 3D printed bio-photoelectrochemical cells through multi-objective Bayesian optimisation
by: JongHyun Kim, et al.
Published: (2025-12-01) -
Multi-objective parametric optimisation of architected hexagonal honeycomb with stepped struts
by: F.I. Azam, et al.
Published: (2025-02-01) -
Multi‐objective multiperiod stable environmental economic power dispatch considering probabilistic wind and solar PV generation
by: Aamir Ali, et al.
Published: (2024-12-01) -
Improving the convergence velocity of the balancing composite motion optimisation algorithm
by: Nang Duc Bui, et al.
Published: (2024-12-01) -
Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration
by: Ghulam Abbas, et al.
Published: (2024-12-01)