材料研究中的可解释机器学习
Explainable Machine Learning in the Research of Materials Science
材料研究中的可解释机器学习 |
| 王冠杰, 刘盛咸, 周健, 孙志梅 |
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Explainable Machine Learning in the Research of Materials Science |
| WANG Guanjie, LIU Shengxian, ZHOU Jian, SUN Zhimei |
| 图9 基于可解释符号回归方法的二维过渡金属硼化物(MBene)单原子催化剂析氧反应(OER)和氧还原反应(ORR)活性预测模型[ |
| Fig.9 Prediction model for oxygen evolution reaction (OER) (a) and oxygen reduction reaction (ORR) (b) reactivity of transition metal boride (MBene) single-atom catalysts based on interpretable symbolic regression (ηORR and ηOER—efficiencies of ORR or OER, respectively; MSE—squared error; MAE—mean absolute error; RMSE—root mean squared error; DFT—density functional theory)[ |
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