Abstract: Subjectivity and uncertainty of risk assessment (RA) procedures can be improved by replacing guesswork with data-driven approaches such as machine learning (ML). Although a plethora of ML prediction techniques have been ...

Abstract: Existing machine learning (ML) delay prediction models cannot process dependencies among the construction progress records. This study investigates graph attention networks (GAT) incorporating multihead attention mechanisms ...

Abstract: Quality is a substantial pillar of construction success, as its failure poses a significant threat to the construction budget and schedule. Effective root cause (RC) analysis allows for the early identification of issues ...

Abstract: Accurate house price prediction allows construction investors to make informed decisions about the housing market and understand the growth opportunities for development and the risks and rewards of different construction ...

Abstract: To reduce the risk of unexpected cost of rework (COR), a variety of predictive models have been developed in the construction management literature. However, they primarily focus on prediction accuracy, and rather less ...