Robotics & Machine Learning Daily News2024,Issue(Jun.18) :95-96.

Study Results from Beihang University Provide New Insights into Machine Learning (A Tensile Properties-related Fatigue Strength Predicted Machine Learning Frame work for Alloys Used In Aerospace)

北航大学的研究结果为机器学习(航空航天用合金拉伸性能相关疲劳强度预测的机器学习框架)提供了新的见解

Robotics & Machine Learning Daily News2024,Issue(Jun.18) :95-96.

Study Results from Beihang University Provide New Insights into Machine Learning (A Tensile Properties-related Fatigue Strength Predicted Machine Learning Frame work for Alloys Used In Aerospace)

北航大学的研究结果为机器学习(航空航天用合金拉伸性能相关疲劳强度预测的机器学习框架)提供了新的见解

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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。摘要:根据NewsRx记者在北京的新闻报道,研究表明:“基于机器学习的(ML)方法,提出了一个与拉伸性能相关的疲劳强度预测框架。首先,收集了包含6种航天材料的200个数据。”这项研究的资金支持包括中国博士后科学基金会,国家创新人才博士后计划。

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, "A tensile properties- related fatigue strength prediction framework based on machine learning (ML) met hods was proposed. Firstly, 200 data containing six materials used in aerospace were collected." Financial supporters for this research include China Postdoctoral Science Founda tion, National Postdoctoral Program for Innovative Talent.

Key words

Beijing/People's Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Beihang University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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