New Study Findings from Universiti Tun Hussein Onn Malaysia Illuminate Research in Machine Learning (Response surface methodology and machine learning optimisat ions comparisons of recycled AA6061-B4C-ZrO2 hybrid metal matrix composites via hot ...)

马来西亚Universiti Tun Hussein Onn Malaysia的新研究结果阐明了机器学习的研究(响应面法和机器学习优化方法对通过热处理回收的AA6061-B4C-ZrO2混合金属基复合材料的比较)

Robotics & Machine Learning Daily News2024，Issue(Jul.1) ：99-100.

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New Study Findings from Universiti Tun Hussein Onn Malaysia Illuminate Research in Machine Learning (Response surface methodology and machine learning optimisat ions comparisons of recycled AA6061-B4C-ZrO2 hybrid metal matrix composites via hot ...)

马来西亚Universiti Tun Hussein Onn Malaysia的新研究结果阐明了机器学习的研究(响应面法和机器学习优化方法对通过热处理回收的AA6061-B4C-ZrO2混合金属基复合材料的比较)

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摘要

由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一份新报告的主题。根据NewsRx编辑在马拉雅柔佛的新闻报道，研究表明，“应用因素重新利用铝AA6061废料的最佳条件是(450、500和550)C预热温度，(1-15)%碳化硼(B4C)和锆(ZrO2)混合增强颗粒，通过热锻(HF)工艺，在120分钟锻造时间。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Johor, Mala ysia, by NewsRx editors, research stated, “The optimal conditions of applied fac tors to reuse Aluminium AA6061 scraps are (450, 500, and 550) C preheating tempe rature, (1-15) % Boron Carbide (B4C), and Zirconium (ZrO2) hybrid reinforced particles at 120 min forging time via Hot Forging (HF) process.”

Key words

Universiti Tun Hussein Onn Malaysia/Joh or/Malaysia/Asia/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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