Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity
Joint Authors
Golnaraghi, Sasan
Zangenehmadar, Zahra
Moselhi, Osama
Alkass, Sabah
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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 product in comparison to planned man-hours.
Productivity is a key element in determining the success and failure of any construction project.
Construction as a labour-driven industry is a major contributor to the gross domestic product of an economy and variations in labour productivity have a significant impact on the economy.
Attaining a holistic view of labour productivity is not an easy task because productivity is a function of manageable and unmanageable factors.
Compound irregularity is a significant issue in modeling construction labour productivity.
Artificial Neural Network (ANN) techniques that use supervised learning algorithms have proved to be more useful than statistical regression techniques considering factors like modeling ease and prediction accuracy.
In this study, the expected productivity considering environmental and operational variables was modeled.
Various ANN techniques were used including General Regression Neural Network (GRNN), Backpropagation Neural Network (BNN), Radial Base Function Neural Network (RBFNN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) to compare their respective results in order to choose the best method for estimating expected productivity.
Results show that BNN outperforms other techniques for modeling construction labour productivity.
American Psychological Association (APA)
Golnaraghi, Sasan& Zangenehmadar, Zahra& Moselhi, Osama& Alkass, Sabah. 2019. Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity. Advances in Civil Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1116603
Modern Language Association (MLA)
Golnaraghi, Sasan…[et al.]. Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity. Advances in Civil Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1116603
American Medical Association (AMA)
Golnaraghi, Sasan& Zangenehmadar, Zahra& Moselhi, Osama& Alkass, Sabah. Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity. Advances in Civil Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1116603
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1116603