Delays and conflicts (D&Cs) are adversely affecting the performance of construction
projects. They have separately been addressed by many authors but the mutual relationship …

Purpose Labour productivity in construction has fallen behind other industries in most of the
world and has declined continuously for decades. Although several scholarly research …

The selection of Global climate models (GCMs) is a major challenge for reliable projection of
climate. A novel method is introduced in this study to select couple model intercomparison …

Selection of appropriate empirical reference evapotranspiration (ETo) estimation models is
very important for the management of agriculture, water resources, and environment …

Selection of appropriate gridded rainfall and temperature data is a key problem for hydro-
climatic studies, particularly in regions where long-term reliable and dense observations are …

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

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 purpose of this paper is to propose a data-driven approach for preparation of
Construction Labour Productivity (CLP) models from influencing labour factors. Two state-of …

Competitiveness is a complex domain with multiple perspectives and a vast range of
definitions, meanings, and measures. Therefore, it is challenging to create an appropriate …

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 …