Web: http://arxiv.org/abs/2206.08011

June 17, 2022, 1:10 a.m. | Zuo Houchen (1), Jiang Yongquan (2), Yang Yan (2), Liu Baoying (2), Hu Jie (1) ((1) State Key Labratory of Traction Power, Southwest Jiaotong Universi

cs.LG updates on arXiv.org arxiv.org

With the rapid development of artificial intelligence, the combination of
material database and machine learning has driven the progress of material
informatics. Because aluminum alloy is widely used in many fields, so it is
significant to predict the properties of aluminum alloy. In this thesis, the
data of Al-Cu-Mg-X (X: Zn, Zr, etc.) alloy are used to input the composition,
aging conditions (time and temperature) and predict its hardness. An ensemble
learning solution based on automatic machine learning and an …

arxiv ensemble learning on prediction

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