Mix Design of Manufactured Sand Concrete Based on Machine Learning Algorithm
FU Chenyang
SUN Xiaoyan
HE Tingquan
LÜ Junxiu
WANG Hailong
Abstract：Five machine learning algorithms were employed to predict the workability and mechanical properties of manufactured sand concrete and a strategy for mix design was proposed using gradient boosting decision tree(GBDT)and XGBoost.Under specific performance requirements,iterative optimization through error analysis yields recommended mix for manufactured sand concrete.The results show that the for manufactured sand concrete produced using the machine-learning-recommended mix has an error of within 10%of the target values,confirming the feasibility of mix design for manufactured sand concrete under specific performance requirements.
Keywords：machine learningmanufactured sand concretemix designGBDT algorithmXGBoost algorithm
Publication Date：2025-07-30
Online Publishing Date：2025-08-18(First online date of this platform, not the publication date of the document)
Pages：9( 678-686 )