Bokor, Orsolya, Florez Perez, Laura, Pesce, Giovanni and Gerami Seresht, Nima (2021) Using Artificial Neural Networks to Model Bricklaying Productivity. In: 2021 European Conference on Computing in Construction. European Council on Computing in Construction (EC3), pp. 52-58. ISBN 9783907234549
|
Text
2021_EC3_Word_Windows_FullPaper_Template_Final_revised.pdf - Accepted Version Download (330kB) | Preview |
Abstract
The pre-planning phase prior to construction is crucial for ensuring an effective and efficient project delivery. Realistic productivity rates forecasted during pre-planning are essential for accurate schedules, cost calculation, and resource allocation. To obtain such productivity rates, the relationships between various factors and productivity need to be understood. Artificial neural networks (ANNs) are suitable for modelling these complex interactions typical of construction activities, and can be used to assist project managers to produce suitable solutions for estimating productivity. This paper presents the steps of determining the network configurations of an ANN model for bricklaying productivity.
Item Type: | Book Section |
---|---|
Uncontrolled Keywords: | artificial neural networks, bricklaying, construction, labour productivity, scheduling |
Subjects: | G700 Artificial Intelligence K900 Others in Architecture, Building and Planning |
Department: | Faculties > Engineering and Environment > Architecture and Built Environment Faculties > Engineering and Environment > Mechanical and Construction Engineering |
Depositing User: | John Coen |
Date Deposited: | 24 Jun 2021 12:29 |
Last Modified: | 07 Oct 2021 13:15 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/46528 |
Downloads
Downloads per month over past year