RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials

The utilization of advanced structural materials, such as preplaced aggregate concrete (PAC), fiber-reinforced concrete (FRC), and FRC beams has revolutionized the field of civil engineering. Therefore, the current research titled "RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials" in Computers and Structures, introduces a novel RAGN-R approach for proposing a comprehensive predictive model. The dataset used for this research is published to be used by researchers, for more, please check the paper.

先进结构材料的应用，例如预置骨料混凝土（preplaced aggregate concrete, PAC）、纤维增强混凝土（fiber-reinforced concrete, FRC）以及FRC梁，已彻底革新了土木工程领域。为此，发表于《计算机与结构（Computers and Structures）》期刊的研究论文《RAGN-R：一种用于预测先进结构材料力学性能的多主体集成机器学习方法》，提出了一种全新的RAGN-R方法以构建全面的预测模型。本研究使用的数据集已公开发布，供广大科研人员使用。如需了解更多细节，请查阅原论文。