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Updated: May 8, 2025

Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

532

全球大数据实验室实验,与基于内核的算法集成,并改进了用于压力强度建模的非线性组合

Babatunde Abiodun Salami1, Jamilu Usman2, Afeez Gbadamosi3

  • 1Cardiff School of Management, Cardiff Metropolitan University, CF5 2YB, Cardiff, Wales, United Kingdom.

Scientific reports
|December 27, 2024
PubMed
概括

这项研究预测了使用混合粘合剂的混凝土压力强度,例如磨砂颗粒高炉渣 (GGBFS) 和飞 (FA). 使用特定输入变量进行支持向量回归 (SVR),准确估计了混凝土性能,为传统水泥提供了可持续的替代方案.

关键词:
混凝土混凝土混凝土混凝土混凝土在地颗粒高炉渣.机器学习是机器学习.强大的线性回归.支持矢量回归的支持矢量回归

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