Studies from Imperial College London Update Current Data on Machine Learning (Pr edictive Modelling of Compressive Strength of Fly Ash and Ground Granulated Blas t Furnace Slag Based Geopolymer Concrete Using Machine Learning Techniques)

伦敦帝国理工学院的研究更新了机器学习的最新数据(使用机器学习技术对粉煤灰和磨细的矿渣基地质聚合物混凝土抗压强度进行预测建模)

Robotics & Machine Learning Daily News2024，Issue(Jul.1) ：117-117.

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Studies from Imperial College London Update Current Data on Machine Learning (Pr edictive Modelling of Compressive Strength of Fly Ash and Ground Granulated Blas t Furnace Slag Based Geopolymer Concrete Using Machine Learning Techniques)

伦敦帝国理工学院的研究更新了机器学习的最新数据(使用机器学习技术对粉煤灰和磨细的矿渣基地质聚合物混凝土抗压强度进行预测建模)

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摘要

由一名新闻记者兼机器人与机器学习每日新闻编辑-研究人员详细介绍了机器学习的新数据。根据NewsRx记者从英国伦敦发回的新闻报道，研究表明：“普通硅酸盐水泥(OPC)对环境有害，为了取代OPC，我们引入了地质聚合物(GPs)。”这项研究的财政支持来自沙特阿拉伯费萨尔国王大学第五届ICE研究生研究和科学研究主席科学研究主任。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, “Ordinary Portland cement (OPC) is proving to be hazardous to the environment. To replace the OPC, geopolymers (GPs) are i ntroduced.” Financial support for this research came from Deanship of Scientific Research, V ice Presidency for Graduate Studies and Scientific Research, King Faisal Univers ity, Saudi Arabia.

Key words

London/United Kingdom/Europe/Cyborgs/Emerging Technologies/Machine Learning/Imperial College London

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出版年

2024

Robotics & Machine Learning Daily News

ISSN：

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