Comparing the Random Forest with the Generalized Additive Model to Evaluate the Impacts of Outdoor Ambient Environmental Factors on Scaffolding Construction Productivity
Publication: Journal of Construction Engineering and Management
Volume 144, Issue 6
Abstract
The improvement of construction productivity has always been a key concern for both researchers and project managers. Several studies have analyzed construction productivity from different perspectives; however, little research has been conducted to evaluate the impact of outdoor ambient environmental factors on construction productivity, especially at the project level. Therefore, to assess such impacts, a nonparametric regression model—the generalized additive model (GAM)—and a nonlinear machine learning model—random forest (RF)—are comparatively used to assess these contributors on the scaffolding construction performance factor (PF). The meteorological variables used in this study include temperature, humidity, ambient pressure, wind speed and wind direction, specific weather event (clear day, fog, rain, or thunderstorm), and the ultraviolet (UV) index. Results demonstrate that the joint meteorological factors play a key role in construction PF variation, with contribution ranging from 32.50% (GAM) to 59.41% (RF). The better performance of RF and GAM shows that the relationship between outdoor ambient environment and construction productivity is nonlinear and should be built by nonlinear models.
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Data Availability Statement
Data analyzed during the study were provided by a third party. Requests for data should be directed to the provider indicated in the Acknowledgements. Information about the Journal’s data sharing policy can be found here: http://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001263.
Acknowledgments
The records on the scaffolding project were provided by KAEFER Integrated Services Pty Ltd. This research was undertaken with the benefit of a grant from the Australian Research Council Linkage Project (No. LP140100873). Our sincere thanks also go to Ms. Angela Wilson for the proofreading she has provided.
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Published In
Journal of Construction Engineering and Management
Volume 144 • Issue 6 • June 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Jun 14, 2017
Accepted: Dec 5, 2017
Published online: Mar 28, 2018
Published in print: Jun 1, 2018
Discussion open until: Aug 28, 2018
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