Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes

The dataset was meticulously compiled from the literature [18,19,28–37,20,38,40–48,21,49–53,69,22–27] resulting in a comprehensive dataset comprising 291 nanomaterial samples and 159 micromaterial samples. This data collection aims to analyze the mechanical properties of UHPC using a wide range of input variables and measuring key output properties. The study results were published under "Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes" in Applied Materials Today.
(Ӧzyüksel Çiftçioğlu A., Kazemi F., & Shafighfard T.(2025). Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes, Applied Materials Today, 102601.)