This review discussed the dilemma of small data faced by materials machine learning. First,
we analyzed the limitations brought by small data. Then, the workflow of materials machine …

Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Using recycled aggregate s from construction and demolition waste can preserve natural
aggregate resources, reduce demand of landfill, and contribute to sustainable built …

This study investigates the non-linear capabilities of two machine learning prediction
models, namely Light GBM and XGBoost, for predicting the values of Rapid Chloride …

This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …

To reduce the environmental impact of construction and demolition waste of concrete,
recycled concrete aggregate (RCA) has been widely utilized in concrete. The compressive …

Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering
applications, and its mechanical properties are crucial for designing and evaluating its …

The compressive strength of fiber-reinforced rubberized recycled aggregate concrete (FR 3
C) is an important performance indicator for its practical application and durability in the …

Data-driven technology such as Artificial Intelligence is considered an essential enabler of
circular economy (CE) in the building construction industry (BCI). As both AI and CE …

Among the many sustainability challenges in the construction industry, those related to the
application of concrete and its components are the most critical. Particularly, the production …