Construction cost predictions to reduce time risk assessment are indispensable steps for
process of decision-making of managers. Machine learning techniques need adequate …

This study reviews the common practices and procedures conducted to identify the cost
drivers that the past literature has classified into two main categories: qualitative and …

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 …

Abstract Decentralizing the Artificial Intelligence (AI) applications is deemed the next wave of
Blockchain Technology (BT) in the construction industry. Most of previous research studies …

Neuro-fuzzy systems (NFS) can explicitly represent and model the input–output
relationships of complex problems and non-linear systems, like those inherent in real-world …

Artificial neural network (ANN) has acquired noticeable interest from the research
community to handle complex problems in Construction and Building engineering (CB). This …

Conceptual cost estimates are important to project feasibility studies and impact upon final
project success. Such estimates provide significant information that can be used in project …

This paper carries out a detailed review of previous studies that employed metaheuristics to
address problems/issues encountered in the life time of a construction or engineering …

Cost estimation is the most important preliminary process in any construction project.
Therefore, construction cost estimation has the lion's share of the research effort in …