[HTML][HTML] Evolution of studies in construction productivity: A systematic literature review (2006–2017)

S Dixit, SN Mandal, JV Thanikal, K Saurabh - Ain Shams engineering …, 2019 - Elsevier
The authors have attempted to summarize the evolution of research in Construction
Productivity (CP) through a Systematic Literature Review (SLR) from the papers published …

Artificial neural networks for construction management: a review

PS Kulkarni, SN Londhe, M Deo - Journal of Soft Computing in Civil …, 2017 - jsoftcivil.com
Construction Management (CM) has to deal with a variety of uncertainties related to Time,
Cost, Quality, and Safety, to name a few. Such uncertainties make the entire construction …

Applying artificial neural networks for measuring and predicting construction-labor productivity

G Heravi, E Eslamdoost - Journal of Construction Engineering and …, 2015 - ascelibrary.org
Variations in labor productivity are the result of multiple influential factors. This paper
attempts to develop a labor productivity model based on multilayer feedforward neural …

Application of artificial neural network (s) in predicting formwork labour productivity

S Golnaraghi, Z Zangenehmadar… - Advances in Civil …, 2019 - Wiley Online Library
Productivity is described as the quantitative measure between the number of resources used
and the output produced, generally referred to man‐hours required to produce the final …

Fuzzy adaptive jellyfish search-optimized stacking machine learning for engineering planning and design

DN Truong, JS Chou - Automation in Construction, 2022 - Elsevier
This paper presents a novel fuzzy adaptive jellyfish search-optimized stacking system (FAJS-
SS) that integrates the jellyfish search (JS) optimizer, the fuzzy adaptive (FA) logic controller …

Dynamic feature selection for accurately predicting construction productivity using symbiotic organisms search-optimized least square support vector machine

MY Cheng, MT Cao, AYJ Mendrofa - Journal of Building Engineering, 2021 - Elsevier
Productivity is one of the crucial elements for managing construction operations effectively
which directly impacts on general cost and time of a project. The accurate prediction of …

Development and comparative of a new meta-ensemble machine learning model in predicting construction labor productivity

I Karatas, A Budak - Engineering, Construction and Architectural …, 2024 - emerald.com
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 …

Predicting the construction labour productivity using artificial neural network and grasshopper optimisation algorithm

P Goodarzizad, E Mohammadi Golafshani… - International Journal …, 2023 - Taylor & Francis
The construction industry is mainly dependent on human resources, and labour costs are
significant. Although many researchers have investigated construction labour productivity …

An integrated simulation and optimization approach for reducing CO2 emissions from on-site construction process in cold regions

HX Li, L Zhang, D Mah, H Yu - Energy and buildings, 2017 - Elsevier
Carbon dioxide (CO 2) reduction has obtained worldwide attention due to the global
warming effects and the mitigating means such as carbon tax. Among the CO 2 emission …

Framework for identifying competencies of construction workers

S Johari, K Neeraj Jha - Journal of Construction Engineering and …, 2021 - ascelibrary.org
Any occupation requires a certain set of competencies at a given employment level.
Although in the construction industry the competency requirements for mid-and upper-level …