Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 20 results ...
Abdalla, A, Li, X and Yang, F (2024) Expatriate construction professionals' performance in international construction projects: The role of cross-cultural adjustment and job burnout. Journal of Construction Engineering and Management, 150(03).
Chen, S, Chen, D, Li, L, Miramini, S and Zhang, L (2024) Optimized bridge maintenance strategies: A system reliability-based approach to enhancing road network performance. Journal of Construction Engineering and Management, 150(03).
Do, Q, Le, T and Le, C (2024) Uncovering critical causes of highway work zone accidents using unsupervised machine learning and social network analysis. Journal of Construction Engineering and Management, 150(03).
Gu, J and Guo, F (2024) Promoting digital sustainability through project digital responsibility implementation: An empirical analysis. Journal of Construction Engineering and Management, 150(03).
Guo, J and Kato, H (2024) Role of government equity investment in capital structure of project finance: Global evidence from PPP projects in developing countries. Journal of Construction Engineering and Management, 150(03).
Halder, A and Batra, S (2024) Navigating the ethical discourse in construction: A state-of-the-art review of relevant literature. Journal of Construction Engineering and Management, 150(03).
Harode, A, Thabet, W and Leite, F (2024) Formulation of feature and label space using modified Delphi in support of developing a machine-learning algorithm to automate clash resolution. Journal of Construction Engineering and Management, 150(03).
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-14167
- Abstract:
To improve the current manual and iterative nature of clash resolution on construction projects, current research efforts continue to explore and test the utilization of machine-learning algorithms to automate the process. Though current research shows significant accuracy in automating clash resolution, many have failed to provide clear explanation and justification for the selection of their feature and label space. Since this is critical in developing an effective and explainable solution in machine learning, it is crucial to address this research gap. In this paper, the authors utilize an in-depth literature review and industry interviews to capture domain knowledge on how design clashes are resolved by industry experts. From analysis of the knowledge captured, we identified 23 factors considered by experts when resolving clashes and five alternative solutions/options to resolve a clash. Using a pool of industry experts, a modified Delphi approach was conducted to validate the factors and options and to determine a priority ranking. The authors identified 94 industry experts based on a predetermined qualification matrix to take part in the modified Delphi. Twelve participants responded and took part in the first round, and 11 completed the second round. A consensus was reached on all clash factors and resolution options. Factors including "clashing elements type,""constrained slope,""critical element in the clash,""location of the clash,""code compliance,"and "project stage clashing element is in"were ranked as the most important factors, while "clashing element material"and "insulation type"were considered the least important. Participants also showed more preference to the "moving the clashing element with low priority in/along x-y-z directions"option to resolve clashes. These identified factors and options will be utilized to collect specific clash data to train and test effective and explainable machine-learning algorithms toward automating clash resolution.
Heydari, M, Heravi, G, Raeisinafchi, R and Karimi, H (2024) A dynamic model to assess the role of site supervision systems in the safety performance of construction projects. Journal of Construction Engineering and Management, 150(03).
Ibrahim, A, Nnaji, C, Namian, M and Shakouri, M (2024) Evaluating the impact of hazard information on fieldworkers' safety risk perception. Journal of Construction Engineering and Management, 150(03).
Ko, T, Lee, J and David Jeong, H (2024) Project requirements prioritization through NLP-driven classification and adjusted work items analysis. Journal of Construction Engineering and Management, 150(03).
Lee, D, Nie, G Y and Han, K (2024) Automatic and real-time joint tracking and three-dimensional scanning for a construction welding robot. Journal of Construction Engineering and Management, 150(03).
Li, Q, Yang, Y, Yao, G, Wei, F, Xue, G and Qin, H (2024) Multiobject real-time automatic detection method for production quality control of prefabricated laminated slabs. Journal of Construction Engineering and Management, 150(03).
Oguz Erkal, E D, Hallowell, M R, Ghriss, A and Bhandari, S (2024) Predicting serious injury and fatality exposure using machine learning in construction projects. Journal of Construction Engineering and Management, 150(03).
Qureshi, A H, Alaloul, W S, Murtiyoso, A, Hussain, S J, Saad, S and Musarat, M A (2024) Automated scaling of point cloud rebar model via aruco-supported controlled markers. Journal of Construction Engineering and Management, 150(03).
Rajabi Asadabadi, M and Zwikael, O (2024) Unrealistic project goals: Detection and modification. Journal of Construction Engineering and Management, 150(03).
Sadeghi, N, Dehghani, M S and Ingolfsson, A (2024) Choice of probability distributions for activity durations in project networks with limited sample size. Journal of Construction Engineering and Management, 150(03).
Seo, W, Kim, B, Bang, S and Kang, Y (2024) Identifying key financial variables predicting the financial performance of construction companies. Journal of Construction Engineering and Management, 150(03).
Tarekegn Gurmu, A and Mahmood, M N (2024) Critical factors affecting quality in building construction projects: Systematic review and meta-analysis. Journal of Construction Engineering and Management, 150(03).
Withrow, J, Dadi, G, Nassereddine, H and Sturgill, R (2024) Asphalt material e-ticketing workflow: Qualitative and quantitative analysis. Journal of Construction Engineering and Management, 150(03).
Zhang, Y, Ren, X, Zhang, J and Ma, Z (2024) A method for deformation detection and reconstruction of shield tunnel based on point cloud. Journal of Construction Engineering and Management, 150(03).