首页|Recent Studies from China University of Mining and Technology Beijing Add New Da ta to Machine Learning (Machine Learningassisted Efficient Design of Cu-based S hape Memory Alloy With Specific Phase Transition Temperature)
Recent Studies from China University of Mining and Technology Beijing Add New Da ta to Machine Learning (Machine Learningassisted Efficient Design of Cu-based S hape Memory Alloy With Specific Phase Transition Temperature)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news originating from Beijing, People’s Republic o f China, by NewsRx correspondents, research stated, “The martensitic transformat ion temperature is the basis for the application of shape memory alloys (SMAs), and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance. In this work, machine learni ng (ML) methods were utilized to accelerate the search for shape memory alloys w ith targeted properties (phase transition temperature).”
BeijingPeople’s Republic of ChinaAsiaAlloysCyborgsEmerging TechnologiesMachine LearningChina University of Mining and Technology Beijing
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