Robotics & Machine Learning Daily News2024,Issue(Nov.13) :34-34.

Studies from Beihang University Yield New Information about Machine Learning (Un derstanding Stacking Fault Energy of Nbmotaw Multi-principal Element Alloys By I nterpretable Machine Learning)

北航大学的研究为机器学习提供了新的信息(用可解释的机器学习理解Nbmotaw多元合金的层错能)

Robotics & Machine Learning Daily News2024,Issue(Nov.13) :34-34.

Studies from Beihang University Yield New Information about Machine Learning (Un derstanding Stacking Fault Energy of Nbmotaw Multi-principal Element Alloys By I nterpretable Machine Learning)

北航大学的研究为机器学习提供了新的信息(用可解释的机器学习理解Nbmotaw多元合金的层错能)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。根据新闻报道NewsRx记者在中华人民共和国北京报道,研究称,“层错”能量(SFE)是影响多主元变形机制的重要性质合金(MPEAs)。然而,通过实验测量MPEAs的SFE和探索MPEAs的复合离子空间还很困难挑战性。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingfrom Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Stacking faultenergy (SFE) is a crucial property influencing the deformation mechanisms of multi-principal elem entalloys (MPEAs). However, experimentally measuring SFE and exploring composit ion space of MPEAs ischallenging.”

Key words

Beijing/People’s Republic of China/Asi a/Alloys/Cyborgs/Emerging Technologies/Machine Learning/Beihang University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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