Robotics & Machine Learning Daily News2024,Issue(Nov.13) :28-28.

Research Conducted at School of Mechanical Sciences Has Updated Our Knowledge ab out Machine Learning (Machine Learning Based Tool for the Efficient Estimation o f Geometric Features of Aggregated Aerosol Particles)

在机械科学学院进行的研究更新了机器学习(基于机器学习的有效估计聚集气溶胶颗粒几何特征的工具)的知识

Robotics & Machine Learning Daily News2024,Issue(Nov.13) :28-28.

Research Conducted at School of Mechanical Sciences Has Updated Our Knowledge ab out Machine Learning (Machine Learning Based Tool for the Efficient Estimation o f Geometric Features of Aggregated Aerosol Particles)

在机械科学学院进行的研究更新了机器学习(基于机器学习的有效估计聚集气溶胶颗粒几何特征的工具)的知识

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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-机器学习的研究结果将在一份新报告中讨论。根据NewsRx记者来自印度果阿的新闻报道,研究称,“虽然意义重大”在气溶胶agg的形成和输运模型的研究方面取得了一些进展仍然需要一种简单、通用的工具来估计聚集粒子的内在性质。标量摩擦因子是气溶胶科学中广泛应用的一个重要参数。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. According tonews reporting originating from Goa, India, by NewsRx correspondents, research stated, “While significantprogress h as been made in developing models for the formation and transport of aerosol agg regates, thereis still a need for a simple, versatile tool capable of estimatin g intrinsic properties of aggregated particles.Scalar friction factor is an imp ortant parameter used extensively in the field of aerosol science.”

Key words

Goa/India/Asia/Cyborgs/Emerging Tech nologies/Machine Learning/School of Mechanical Sciences

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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