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Estimation of construction waste composition based on bulk density: A big data-probability (BD-P) model
Journal of Environmental Management
◽
10.1016/j.jenvman.2021.112822
◽
2021
◽
Vol 292
◽
pp. 112822
Author(s):
Liang Yuan
◽
Weisheng Lu
◽
Fan Xue
Keyword(s):
Big Data
◽
Bulk Density
◽
Construction Waste
◽
Waste Composition
Download Full-text
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References
Investigating the bulk density of construction waste: A big data-driven approach
Resources Conservation and Recycling
◽
10.1016/j.resconrec.2021.105480
◽
2021
◽
Vol 169
◽
pp. 105480
Author(s):
Weisheng Lu
◽
Liang Yuan
◽
Fan Xue
Keyword(s):
Big Data
◽
Bulk Density
◽
Data Driven
◽
Construction Waste
◽
Data Driven Approach
Download Full-text
Construction Waste Generation Rate (WGR) Revisited: A Big Data Approach
Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate
◽
10.1007/978-3-662-46994-1_69
◽
2015
◽
pp. 843-854
◽
Cited By ~ 2
Author(s):
Xi Chen
◽
Weisheng Lu
◽
Meng Ye
◽
Liyin Shen
Keyword(s):
Big Data
◽
Generation Rate
◽
Waste Generation
◽
Construction Waste
◽
Waste Generation Rate
Download Full-text
Data from: Benchmarking construction waste management performance using big data
10.5353/ds_dataset103740
◽
2013
◽
Author(s):
W Lu
Keyword(s):
Big Data
◽
Waste Management
◽
Management Performance
◽
Construction Waste
Download Full-text
The effects of green building on construction waste minimization: Triangulating ‘big data’ with ‘thick data’
Waste Management
◽
10.1016/j.wasman.2018.07.030
◽
2018
◽
Vol 79
◽
pp. 142-152
◽
Cited By ~ 16
Author(s):
Weisheng Lu
◽
Xi Chen
◽
Yi Peng
◽
Xingjian Liu
Keyword(s):
Big Data
◽
Green Building
◽
Waste Minimization
◽
Construction Waste
Download Full-text
An off-site snapshot methodology for estimating building construction waste composition - a case study of Hong Kong
Environmental Impact Assessment Review
◽
10.1016/j.eiar.2019.03.006
◽
2019
◽
Vol 77
◽
pp. 128-135
◽
Cited By ~ 24
Author(s):
Zezhou Wu
◽
Ann T.W. Yu
◽
Chi Sun Poon
Keyword(s):
Hong Kong
◽
Building Construction
◽
Construction Waste
◽
Waste Composition
Download Full-text
Big data architecture for construction waste analytics (CWA): A conceptual framework
Journal of Building Engineering
◽
10.1016/j.jobe.2016.03.002
◽
2016
◽
Vol 6
◽
pp. 144-156
◽
Cited By ~ 53
Author(s):
Muhammad Bilal
◽
Lukumon O. Oyedele
◽
Olugbenga O. Akinade
◽
Saheed O. Ajayi
◽
Hafiz A. Alaka
◽
...
Keyword(s):
Big Data
◽
Conceptual Framework
◽
Construction Waste
◽
Data Architecture
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Analysis of the construction waste management performance in Hong Kong: the public and private sectors compared using big data
Journal of Cleaner Production
◽
10.1016/j.jclepro.2015.06.106
◽
2016
◽
Vol 112
◽
pp. 521-531
◽
Cited By ~ 53
Author(s):
Weisheng Lu
◽
Xi Chen
◽
Daniel C.W. Ho
◽
Hongdi Wang
Keyword(s):
Big Data
◽
Hong Kong
◽
Waste Management
◽
Management Performance
◽
Public And Private
◽
Construction Waste
◽
The Public
Download Full-text
Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data
International Journal of Sustainable Building Technology and Urban Development
◽
10.1080/2093761x.2015.1116415
◽
2015
◽
Vol 6
(4)
◽
pp. 211-228
◽
Cited By ~ 26
Author(s):
Muhammad Bilal
◽
Lukumon O. Oyedele
◽
Junaid Qadir
◽
Kamran Munir
◽
Olugbenga O. Akinade
◽
...
Keyword(s):
Big Data
◽
Waste Minimization
◽
Construction Waste
Download Full-text
Benchmarking construction waste management performance using big data
Resources Conservation and Recycling
◽
10.1016/j.resconrec.2015.10.013
◽
2015
◽
Vol 105
◽
pp. 49-58
◽
Cited By ~ 54
Author(s):
Weisheng Lu
◽
Xi Chen
◽
Yi Peng
◽
Liyin Shen
Keyword(s):
Big Data
◽
Waste Management
◽
Management Performance
◽
Construction Waste
Download Full-text
Is the private sector more efficient? Big data analytics of construction waste management sectoral efficiency
Resources Conservation and Recycling
◽
10.1016/j.resconrec.2019.104674
◽
2020
◽
Vol 155
◽
pp. 104674
◽
Cited By ~ 2
Author(s):
Jinying Xu
◽
Weisheng Lu
◽
Meng Ye
◽
Fan Xue
◽
Xiaoling Zhang
◽
...
Keyword(s):
Big Data
◽
Waste Management
◽
Private Sector
◽
Data Analytics
◽
Big Data Analytics
◽
Construction Waste
Download Full-text
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