Studies from University of Queensland Have Provided New Data on Machine Learning (Investigation of Age-hardening Behaviour of Al Alloys Via Feature Screening-as sisted Machine Learning)
Studies from University of Queensland Have Provided New Data on Machine Learning (Investigation of Age-hardening Behaviour of Al Alloys Via Feature Screening-as sisted Machine Learning)
昆士兰大学的研究提供了机器学习的新数据（通过特征筛选研究铝合金的时效硬化行为&辅助机器学习）
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摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-研究人员详细介绍机器学习中的新数据。根据新闻报道澳大利亚圣卢西亚，NewsRx Ed Itors的研究表明，“时效硬化是一种至关重要的强化措施。”铝(Al)合金的工艺。然而，按照传统方法确定最佳老化条件h依靠资源密集型的试错方法。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Researchers detail new data in Machine Learning. According to news reporting out ofSt. Lucia, Australia, by NewsRx ed itors, research stated, “Age hardening stands as a crucial strengtheningprocess for aluminium (Al) alloys. However, determining the optimal ageing conditions h as traditionallyrelied on resource-intensive trial-and-error methods.”
Key words
St. Lucia/Australia/Australia and New Zealand/Alloys/Cyborgs/Emerging Technologies/Machine Learning/University of Queensland
NETL
NSTL