Abstract Graph Neural Networks (GNNs) have emerged as a promising solution for
effectively handling non-Euclidean data in construction, including building information …

Machine Learning (ML), a subset of Artificial Intelligence (AI), is gaining popularity in the
architectural, engineering, and construction (AEC) sector. This systematic study aims to …

Optimizing work package schemes is challenging under uncertain task duration. This paper
develops a two-list genetic algorithm (TLGA) to optimize work package schemes with …

Effective construction project planning relies on addressing constraints related to materials,
labor, equipment, and others. Planning meetings are typical venues for stakeholders to …

Abstract Machine learning models have seen widespread application in predicting building
thermal loads. Yet, these existing models generally predict the thermal load for a single …

The inherent uncertainty and complexity of infrastructure systems present significant
challenges for precise management. By providing real-time status tracking and decision …

Artificial intelligence covers a variety of methods and disciplines including vision, perception,
speech and dialogue, decision making and planning, problem solving, robotics and other …

Recent advances in robotics have enabled robots to collaborate with workers in shared,
fenceless workplaces in construction and civil engineering, which can improve productivity …

Recent advancements in computer vision and augmented reality (AR) technology have
created a pathway for enhanced human–computer interaction. Despite the potential …

The construction material quantity (CMQ) is widely concerned in the structural design of
reinforced concrete buildings and is often included among the objective functions of …