摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx记者从哈尔滨发回的新闻报道，研究表明：“本文采用机器学习加速密度泛函理论，系统地研究了合金原子在铝基和不同类型石墨烯/铝界面中的扩散迁移行为，并通过第一性原理计算建立了小样本数据集。”输入和输出特征值的类型由特征工程确定，考虑到模式L复杂性和预测精度的影响，最终确定完美界面、缺陷界面和铝基体的输入特征数量为6、5和4.本研究经费来源于特殊环境下先进复合材料国家重点科学技术实验室科学基金。
Abstract
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.
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