摘要
由一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-关于人工智能的最新研究结果已经发表。根据NewsRx编辑来自Ombia Medellin的新闻，该研究称，"混凝土生产过程涉及水泥、水和其他材料的混合。"这项研究的财政支持者包括哥伦比亚Minciencias。新闻记者从Ificia Bolivariana大学的研究中获得了一句话：“每种材料的数量导致的性能特别按照压缩或弯曲强度H来估计。已经观察到混凝土的最终性能具有很高的瓦里安CE，传统的配方方法不能保证一致的结果。因此，设计往往过度设计。产生比要求更高的成本，以确保向客户承诺的性能。本研究建议构建预测机器学习模型，以估计抗压或弯曲强度和混凝土坍落度。本研究采用TEAM数据科学过程(TDSP)方法，使用Co Lombian Ready Mix(RMX)Company Cementos Argos S.A.在五年内生成的数据集，包含用于不同混凝土混合物的材料数量，以及在实验室测量的性能指标。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news originating from Medellin, Col ombia, by NewsRx editors, the research stated, “The process of concrete producti on involves mixing cement, water, and other materials.” Financial supporters for this research include Minciencias Colombia. The news correspondents obtained a quote from the research from Universidad Pont ificia Bolivariana: “The quantity of each of these materials results in a perfor mance that is particularly estimated in terms of compressive or flexural strengt h. It has been observed that the final performance of concrete has a high varian ce and that traditional formulation methods do not guarantee consistent results. Consequently, designs tend to be over-designed, generating higher costs than re quired, to ensure the performance committed to the client. This study proposes t he construction of predictive machine learning models to estimate compressive or flexural strength and concrete slump. The study was carried out following the T eam Data Science Process (TDSP) methodology, using a dataset generated by the Co lombian Ready Mix (RMX) company Cementos Argos S.A. over five years, containing the quantity of materials used for different concrete mixes, as well as performa nce metrics measured in the laboratory.”
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