Robotics & Machine Learning Daily News2024,Issue(Nov.29) :24-25.

Studies from Wuhan Textile University Yield New Information about Machine Learni ng (Comparative Study of Machine Learning Method and Response Surface Methodolog y In Bga Solder Joint Parameter Optimization)

武汉纺织大学的研究为机器学习提供了新的信息(机器学习方法与响应面法在Bga焊点参数优化中的比较研究)

Robotics & Machine Learning Daily News2024,Issue(Nov.29) :24-25.

Studies from Wuhan Textile University Yield New Information about Machine Learni ng (Comparative Study of Machine Learning Method and Response Surface Methodolog y In Bga Solder Joint Parameter Optimization)

武汉纺织大学的研究为机器学习提供了新的信息(机器学习方法与响应面法在Bga焊点参数优化中的比较研究)

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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-调查人员发布马学习的新报告。根据新闻报道来自中国人民代表大会武汉,由NewsRx记者报道,研究称:“球”网格阵列(BGA)封装在热振动耦合环境中容易出现故障问题,例如焊点的变形和断裂。焊点最小等效应力的预测本文旨在比较机器学习方法和传统的机器学习方法,更准确地优化焊点结构响应冲浪ACE方法(RSM)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingoriginating from Wuhan, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Ballgrid array (BGA ) package is prone to failure issues in a thermal vibration-coupled environment, suchas deformation and fracture of solder joints. To predict the minimum equiv alent stress of solder jointsmore accurately and optimize the solder joint stru cture, this paper aims to compare the machine learningmethod with response surf ace methodology (RSM).”

Key words

Wuhan/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Wuhan Textile University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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