Robotics & Machine Learning Daily News2024,Issue(Jul.1) :142-143.

Investigators from Opole University of Technology Release New Data on Machine Le arning (A Study On Friction Induced Tribological Characteristics of Steel 316 L Against 100 Cr6 Alloy Under Different Lubricating Conditions With Machine Learni ng ...)

Opole理工大学的研究人员发布了机器学习的新数据(用机器学习研究316l钢与100 Cr6合金在不同润滑条件下的摩擦诱导摩擦学特性)

Robotics & Machine Learning Daily News2024,Issue(Jul.1) :142-143.

Investigators from Opole University of Technology Release New Data on Machine Le arning (A Study On Friction Induced Tribological Characteristics of Steel 316 L Against 100 Cr6 Alloy Under Different Lubricating Conditions With Machine Learni ng ...)

Opole理工大学的研究人员发布了机器学习的新数据(用机器学习研究316l钢与100 Cr6合金在不同润滑条件下的摩擦诱导摩擦学特性)

扫码查看

摘要

一位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-在一份新的报告中讨论了机器学习的研究结果。根据来自波兰奥波尔的新闻,NewsRx的记者报道,研究表明:“当两个固体实体不断地向另一个实体运动时,材料从接触表面稳定磨损。当涉及更多参数和极端材料时,很难分析和观察摩擦磨损现象。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news originating from Opole, Poland, by NewsRx correspondents, research stated, “The material steadily wears away fr om touching surfaces when two solid entities are constantly moving against one o ther. When more parameters and extreme materials are involved in tribological te sting, then it is very difficult to analyze and observe the working phenomena.”

Key words

Opole/Poland/Europe/Cyborgs/Emerging Technologies/Machine Learning/Opole University of Technology

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文