Reports Outline Machine Learning Findings from Polytechnic University Milan (Exploratory Analysis and Evolutionary Computing Coupled Machine Learning Algorithms for Modelling the Wear Characteristics of Az31 Alloy)

Robotics & Machine Learning Daily News2024，Issue(Jan.2) ：48-49.

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Reports Outline Machine Learning Findings from Polytechnic University Milan (Exploratory Analysis and Evolutionary Computing Coupled Machine Learning Algorithms for Modelling the Wear Characteristics of Az31 Alloy)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators discuss new findings in Machine Learning. According to news originating from Milan,Italy, by NewsRx correspondents, research stated, “The wear resistance of magnesium alloys is one of itskey technological properties that could limit their practical application. In accordance with ASTM G99-95astandard, this study used a pin-on-disc method to analyze the wear behavior of ascast AZ31 magnesiumalloy under dry-sliding conditions.”

Key words

Milan/Italy/Europe/Algorithms/Cyborgs/Emerging Technologies/Light Metals/Machine Learning/Magnesium/Particle Swarm Optimization/Polytechnic University Milan

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出版年

2024

Robotics & Machine Learning Daily News

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