首页|Findings from China Iron and Steel Research Institute Group Provide New Insights into Machine Learning (Prediction of Magnetocaloric Properties of Fe-based Amorphous Alloys Based On Interpretable Machine Learning)
Findings from China Iron and Steel Research Institute Group Provide New Insights into Machine Learning (Prediction of Magnetocaloric Properties of Fe-based Amorphous Alloys Based On Interpretable Machine Learning)
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NETL
NSTL
Elsevier
Investigators publish new report on Machine Learning. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “This study developed a machine learning model to accurately predict the isothermal magnetic entropy change (-SM) in amorphous alloys, a key parameter for evaluating magnetocaloric performance. Four machine learning algorithms were compared, and the (Extremely Randomized Trees) ETR algorithm demonstrated exceptional performance with an (R-squared) R2 value of 0.90 and a (Mean Absolute Percentage Error) MAPE of 13.31 % on the test set.” Financial support for this research came from National Key Research and Development Program of China.
BeijingPeople’s Republic of ChinaAsiaAlloysCyborgsEmerging TechnologiesMachine LearningChina Iron and Steel Research Institute Group
NETL
NSTL
Elsevier
