基于Bayesian采样主动机器学习模型的6061铝合金成分精细优化
Composition Refinement of 6061 Aluminum Alloy Using Active Machine Learning Model Based on Bayesian Optimization Sampling
(a) Si (b) Cu (c) Mn (d) Mg (e) Ti (f) Fe (g) Zn (h) Cr
基于Bayesian采样主动机器学习模型的6061铝合金成分精细优化 |
| 赵婉辰, 郑晨, 肖斌, 刘行, 刘璐, 余童昕, 刘艳洁, 董自强, 刘轶, 周策, 吴洪盛, 路宝坤 |
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Composition Refinement of 6061 Aluminum Alloy Using Active Machine Learning Model Based on Bayesian Optimization Sampling |
| ZHAO Wanchen, ZHENG Chen, XIAO Bin, LIU Xing, LIU Lu, YU Tongxin, LIU Yanjie, DONG Ziqiang, LIU Yi, ZHOU Ce, WU Hongsheng, LU Baokun |
| 图9 微量元素特征与硬度之间的绝对变化规律及贡献性分析 (a) Si (b) Cu (c) Mn (d) Mg (e) Ti (f) Fe (g) Zn (h) Cr |
| Fig.9 Absolute influence of trace element features on hardness (blue shade—confidence interval, red line—baseline value) |
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