Fuzzy and hybrid methods have been increasingly used in construction risk management
research and this study aims to compile and analyse the basic concepts and methods …

Purpose In the past decades, artificial intelligence (AI)-based hybrid methods have been
increasingly applied in construction risk management practices. The purpose of this paper is …

In this paper, we compared the predictive capabilities of six different machine learning
algorithms–linear regression, artificial neural network, random forest, extreme gradient …

A better understanding of top-down estimating practices and their contribution to budgeting
accuracy allows public transportation agencies to allocate limited construction funds more …

The construction industry including its support industries is one of the highest consumers of
natural resources. In the act of consumption of natural resources during construction …

Low accuracy in the estimation of construction costs at early stages of projects has driven
the research on alternative costing methods that take advantage of computing advances …

Purpose Bayesian approaches have been widely applied in construction management (CM)
research due to their capacity to deal with uncertain and complicated problems. However, to …

The meaningful quantification of uncertainty in hydrological model outputs is a challenging
task since complete knowledge about the hydrologic system is still lacking. Owing to the …

With the increasing complexity of problems in the construction industry, researchers are
investigating computationally rigorous intelligent systems with the aim of seeking intelligent …

Completing a project within the planned budget is the bottom-line of construction
companies. To achieve this goal, periodic cost estimation is vitally important not only in the …