Purpose The performance-based utilisation of labour resources is a decisive function for
developing characteristics of the next normal in the construction industry. Based on the …

Purpose This study reviews the extent of application of artificial intelligence (AI) tools in the
construction industry. Design/methodology/approach A thorough literature review (based on …

Construction productivity estimation lacks a comprehensive, standard, and task-type-
independent framework to generate and serialize Machine Learning (ML) models. This …

The performance of labour is one of the most important factors affecting the physical
progress of any construction project. This study intended to extensively investigate on the …

The selection of global climate models (GCMs) for a region remained a difficult step in
climate change studies. A state-of-the-art Support Vector Machine Recursive Feature …

Purpose This study focused on exploring the performance factors (PFs) that impact
Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold …

Purpose The study is aimed to compare the prediction success of basic machine learning
and ensemble machine learning models and accordingly create novel prediction models by …

Abstract The Sri Lankan construction industry has experienced rapid development in the
post-war era due to new trends in the country. Currently, the construction industry in the …

The factors that affect productivity are a major focus in construction. This article proposes a
machine learning–based approach to predict task productivity by using a subjective …

This paper presents a novel approach, using hybrid feature selection (HFS), machine
learning (ML), and particle swarm optimization (PSO) to predict and optimize construction …