Findings from Songshan Lake Materials Laboratory Reveals New Findings on Machine Learning (Optimizing the Mechanical Performance of A356-sc-sr Alloy Via Combini ng Machine Learning and Mechanical Stirring Under Vacuum)

Robotics & Machine Learning Daily News2024，Issue(Jul.11) ：68-68.

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Findings from Songshan Lake Materials Laboratory Reveals New Findings on Machine Learning (Optimizing the Mechanical Performance of A356-sc-sr Alloy Via Combini ng Machine Learning and Mechanical Stirring Under Vacuum)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news originatingfrom Dongguan, People’s Republic o f China, by NewsRx correspondents, research stated, “In this study,a machine le arning design system (MLDS) with a property-oriented optimization strategy was f irstestablished to predict the mechanical properties of the A356 alloys with ad ding Sc and Sr elements. Basedon the experimental verification from the MLDS, t he addition of 0.2 wt% Sc and 0.067 wt% Sr elementsled to the refinement of alpha-Al grains and eutectic Si phases.”

Key words

Dongguan/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Songshan Lake Materials La boratory

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出版年

2024

Robotics & Machine Learning Daily News

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