Development of a Machine-Learning Enhanced Modular Residential Construction Direct Cost Estimation Method

被引:1
作者
Aswin, Ramaswamy Govindan [1 ]
Qiu, Changcui [1 ]
Zhang, Bo [2 ]
Li, Xinming [1 ]
机构
[1] Univ Alberta, Dept Mech Engn, Edmonton, AB, Canada
[2] Univ Alberta, Dept Civil & Environm Engn, Edmonton, AB, Canada
来源
PROCEEDINGS OF THE CANADIAN SOCIETY FOR CIVIL ENGINEERING ANNUAL CONFERENCE, VOL 3, CSCE 2023 | 2024年 / 497卷
关键词
Cost estimation; Construction project; Machine learning; Cost monitoring; Direct cost prediction; NEURAL-NETWORKS; REGRESSION-ANALYSIS; BUILDING-PROJECTS; MODELS;
D O I
10.1007/978-3-031-62170-3_25
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Direct cost estimation is beneficial in residential construction projects because it enables decision-makers to proactively manage project costs, which can result in the successful completion of the project. Currently, traditional bottom-up cost estimation used for modular residential construction projects is a time-consuming and knowledge-intensive procedure. In contrast to bottom-up cost estimation, using machine learning techniques for initial construction cost estimation can significantly overcome these drawbacks and help decision-makers effectively perform proactive cost management. Machine learning has been successfully used in studies before for this purpose, but not for projects involving the construction of modular homes. This study therefore employs and validates the use of machine learning to estimate direct costs (direct material costs and direct labour costs) in order to quickly, accurately, and conveniently estimate costs for modular residential construction projects.
引用
收藏
页码:353 / 368
页数:16
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