Findings in the Area of Machine Learning Reported from Beijing University of Che mical Technology (Physics-informed Machine Learning Approach for Molten Pool Mor phology Prediction and Process Evaluation In Directed Energy Deposition of 12crn i2 ...)

北京化工大学在机器学习领域的研究成果(12crn i2定向能沉积熔池形貌预测和工艺评价的物理信息机器学习方法...)

Robotics & Machine Learning Daily News2024，Issue(Jun.19) ：115-116.

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Findings in the Area of Machine Learning Reported from Beijing University of Che mical Technology (Physics-informed Machine Learning Approach for Molten Pool Mor phology Prediction and Process Evaluation In Directed Energy Deposition of 12crn i2 ...)

北京化工大学在机器学习领域的研究成果(12crn i2定向能沉积熔池形貌预测和工艺评价的物理信息机器学习方法...)

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-调查人员讨论机器学习的新发现。根据《中国人民日报》记者在北京的新闻报道，研究表明：“中国学习(ML)的进步为定向能沉积(DED)添加剂制造(AM)过程中的现场监测和反馈控制提供了可能，但要获得足够高质量的实验样本是昂贵的，不可行的。”国家自然科学基金(NSFC)、四川省重点研究开发项目、国家重点研究开发项目等资助项目。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating in Beijing, People's R epublic of China, by NewsRx journalists, research stated, "The advancement of ma chine learning (ML) provides possibilities for in-situ monitoring and feedback c ontrol during directed energy deposition (DED) additive manufacturing (AM) proce ss. However, obtaining sufficient and high-quality training samples experimental ly is expensive and infeasible." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Key Research and Development Program of Sichuan Province, Na tional Key Research and Development Program of China.

Key words

Beijing/People's Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Beijing University of Chemi cal Technology

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出版年

2024

Robotics & Machine Learning Daily News

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