首页|Studies from Harbin Institute of Technology in the Area of Machine Learning Desc ribed (Explainable Machine Learning Accelerated Density Functional Theory Predic tion for Diffusive Transport Behaviour of Elements In Aluminium Matrix and ...)
Studies from Harbin Institute of Technology in the Area of Machine Learning Desc ribed (Explainable Machine Learning Accelerated Density Functional Theory Predic tion for Diffusive Transport Behaviour of Elements In Aluminium Matrix and ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Harbin, Pe ople’s Republic of China, by NewsRx correspondents, research stated, “In this pa per, the diffusive migration behaviour of alloy atoms in aluminium matrix and di fferent types of graphene/aluminium interfaces is systematically investigated by using a machine learning accelerated density functional theory. A small sample dataset is established by first principles calculation, the types of input and o utput eigenvalues are determined by feature engineering, and the number of input features for perfect interfaces, defective interfaces, and aluminium matrix are finally determined to be 6, 5, and 4 by taking into account the effects of mode l complexity and prediction accuracy.” Financial support for this research came from Science foundation of national key laboratory of science and technology on advanced composites in special environm ents.
HarbinPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHarbin Institute of Technolo gy
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