Achieving sustainable green building design is essential to reducing our environmental
impact and enhancing energy efficiency. Traditional methods often depend heavily on …

Membraneless microfluidic fuel cells (MMFCs) offer great potential for clean energy
production, but their expense and tedious optimization process have limited their wider use …

The building industry generates large amounts of solid waste due to construction,
maintenance, or demolition activities. Although the construction and demolition waste is well …

Purpose This paper aims to clarify the efficient process of the machine learning algorithms
implemented in the ready-mix concrete (RMC) onsite. It proposes innovative machine …

Linear construction projects, such as pipeline irrigation projects, are prone to delays and
cost overruns owing to inaccurate cost and duration estimates. The research gap pertains to …

The artificial neural networks (ANNs)-based model has been used to predict the
compressive strength of concrete, assisting in creating recycled aggregate concrete mixtures …

Continuously, cost overruns in construction projects, as a leading cause of project failure,
have been attracting more and more attention among construction stakeholders. Notably …

Over the past few decades, the construction industry has been suffering from project delays.
It remains a recognized challenge to accurately predict the actual project's progress, despite …

Purpose This study aims at proposing a hybrid model for early cost prediction of a
construction project. Early cost prediction for a construction project is the basic approach to …

Purpose The present study aims to develop a risk-supported case-based reasoning (RS-
CBR) approach for water-related projects by incorporating various uncertainties and risks in …