Robotics & Machine Learning Daily News2024,Issue(Dec.4) :183-183.

Reports Summarize Machine Learning Study Results from Free University of Bozen ( Modelling the Effective Thermal Conductivity and Porosity of an Open-cell Materi al Using an Image-based Technique Coupled With Machine Learning)

报告总结了博岑自由大学的机器学习研究结果(使用基于图像的技术结合机器学习来模拟开孔材料的有效导热率和孔隙率)

Robotics & Machine Learning Daily News2024,Issue(Dec.4) :183-183.

Reports Summarize Machine Learning Study Results from Free University of Bozen ( Modelling the Effective Thermal Conductivity and Porosity of an Open-cell Materi al Using an Image-based Technique Coupled With Machine Learning)

报告总结了博岑自由大学的机器学习研究结果(使用基于图像的技术结合机器学习来模拟开孔材料的有效导热率和孔隙率)

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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-关于机器学习的详细数据已经呈现。根据新闻报道这项研究源于意大利博尔扎诺,由NewsRx编辑撰写,它指出:“有效导热系数是是绝缘材料表征中最重要的参数之一。开孔多孔材料的有效导热系数受其微观结构和微观结构的影响固相和液相的类型呈现出来。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating from Bolzano, Italy, by NewsRx editors, the research stated, “Effective thermal conductivity isconside red one of the most important parameters in the characterization of insulating m aterials. Theeffective thermal conductivity of open-cell porous materials is in fluenced by both their microstructure andthe types of solid and fluid phases pr esent.”

Key words

Bolzano/Italy/Europe/Cyborgs/Emergin g Technologies/Machine Learning/Free University of Bozen

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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