首页|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)
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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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.”
DongguanPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningSongshan Lake Materials La boratory
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