首页|Studies from Northeastern University Further Understanding of Machine Learning (Machine Learning Informed Tetragonal Ratio C/a of Martensite)
Studies from Northeastern University Further Understanding of Machine Learning (Machine Learning Informed Tetragonal Ratio C/a of Martensite)
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NETL
NSTL
Elsevier
Researchers detail new data in Machine Learning. According to news reporting from Shenyang, People's Republic of China, by NewsRx journalists, research stated, "Tetragonal ratio (c/a) is a critical structural parameter that heavily decides plenty of performances of tetragonal martensitic materials. Nevertheless, the knowledge about c/a remains limited and there is still no definitive strategy to tailor it." Financial supporters for this research include National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central Universities, Ministry of Education, China - 111 Project.
ShenyangPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNortheastern University
NETL
NSTL
Elsevier
