研究论文
Rapid design of processing parameters for Zero-Sample alloys via multi-acquisition-function Bayesian optimization
Jingtai Sun, Huadong Fu, Hongtao Zhang, Menghe Zhao, Peiwen Yun, Jianxin Xie
University of Science and Technology Beijing Liaoning Academy of Materials Beijing Laboratory of Metallic Materials and Processing for Modern Transportation
来源Materials Science and Engineering A
年份2025
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材料 / 化学Machine Learning in Materials Science
Optimal Experimental Design Methods · Advanced Multi-Objective Optimization Algorithms
参考文献 52
Studies on recrystallization of single-phase copper alloys by resistance measurements
被引 75Jens Freudenberger, Alexander Kauffmann, H.-J. Klauß · Acta Materialia · 2010
The use of flat-ended projectiles for determining dynamic yield stress I. Theoretical considerations
被引 640Geoffrey Ingram Taylor · Proceedings of the Royal Society of London A Mathematical and Physical Sciences · 1948
High strength and ductile ultrafine-grained Cu–Ag alloy through bimodal grain size, dislocation density and solute distribution
被引 132Sitarama Raju Kada, V. Subramanya Sarma, Alexander Kauffmann · Acta Materialia · 2012
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引用本文 5
Investigating the effects of extrusion temperature and speed on the mechanical properties of high-strength Al-Mg-Si alloys using machine learning methods
被引 2Jie Li, Lingying Ye, Yu Wang · Materials Science and Engineering A · 2026
Active learning for the design of Al-Mg-Si alloys with optimized strength-ductility balance
被引 1Jun Li, Haotian Deng, Hao Liu · Journal of Alloys and Compounds · 2026
Data-driven optimization of two-stage deformation-aging parameters enhances mechanical and electrical properties of Cu-Ni-Si-Cr alloy
被引 1Jinyu Liang, Fan Zhao, Guoliang Xie · Materials Science and Engineering A · 2026
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