Abstract
Formwork installation, rebar fabrication/installation, and concrete casting are often repetitive in high-rise building projects. Previous studies have shown that labor productivity is significantly affected by many reasons. This study aims to consider the relationship between average
labor productivity and design characteristics in typical floors of high-rise building projects. Data were collected through questionnaire which was distributed to experts and experienced people in construction projects. A neural network model was developed to estimate labor productivity.
The main result is the comparison between predicted and actual labor productivity for typical floors. The Mean Absolute Percentage Errors (MAPE) are less than 3.5%, and R-squared indices are greater than 85% for all three activities mentioned above. These results showed that the
model developed in this study is very appropriate when predicting labor productivity in high-rise building projects.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Ha, Duy Khanh hd.khanh@hotmail.com Lee, Young Dai UNSPECIFIED Kim, Soo Yong UNSPECIFIED |
Subjects: | H Social Sciences > HD Industries. Land use. Labor > Management. Industrial Management > Industrial productivity > Labor productivity N Fine Arts > NA Architecture > Public buildings > Commercial buildings > Office buildings. Skyscrapers Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science) |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Architecture, Planning and Surveying |
Journal or Publication Title: | Built Environment Journal (BEJ) |
UiTM Journal Collections: | UiTM Journal > Built Environment Journal (BEJ) |
ISSN: | 1675-5022 |
Volume: | 11 |
Number: | 1 |
Page Range: | pp. 15-28 |
Keywords: | Labor productivity, High-rise building, Design characteristics, Artificial neural network, Vietnam |
Date: | 2014 |
URI: | https://ir.uitm.edu.my/id/eprint/13619 |