Items with Index Term: decision tree

Abbasianjahromi, H and Aghakarimi, M (2023) Safety performance prediction and modification strategies for construction projects via machine learning techniques. Engineering, Construction and Architectural Management, 30(3), pp. 1146-1164. ISSN 0969-9988

Abdelgawad, M A M (2011) Hybrid decision support system for risk criticality assessment and risk analysis. PhD thesis, University of Alberta, Canada.

Ahmed, Q A (1993) A knowledge-based system approach to work shift selection for multilane highway reconstruction and maintenance projects. PhD thesis, University of Florida, USA.

Al-Aomar, R; AlTal, M and Abel, J (2024) A data-driven predictive maintenance model for hospital HVAC system with machine learning. Building Research & Information, 52(1-2), pp. 207-224. ISSN 0961-3218

Alaka, H A (2017) 'Big data analytics' for construction firms insolvency prediction models. PhD thesis, University of the West of England, Bristol, UK.

Alshboul, O; Shehadeh, A; Al-Kasasbeh, M; Al Mamlook, R E; Halalsheh, N and Alkasasbeh, M (2022) Deep and machine learning approaches for forecasting the residual value of heavy construction equipment: A management decision support model. Engineering, Construction and Architectural Management, 29(10), pp. 4153-4176. ISSN 0969-9988

Andalib, M (2026) Predictive modelling for contract selection in construction through data mining and machine learning: Insights from agency theory. International Journal of Construction Education and Research, 22(1), pp. 138-163. ISSN 1557-8771

Assaad, R H; Omran, A; Soliman, N and Assaf, G (2024) Prediction of the lateral pressure of self-consolidating concrete on construction formwork systems using machine-learning algorithms. Journal of Construction Engineering and Management, 150(9): 04024110, ISSN 0733-9364

Awe, O O; Atofarati, E O; Adeyinka, M O; Musa, A P and Onasanya, E O (2024) Assessing the factors affecting building construction collapse casualty using machine learning techniques: A case of Lagos, Nigeria. International Journal of Construction Management, 24(3), pp. 261-269. ISSN 1562-3599

Basaran, Y.; Aladag, H. and Isik, Z. (2026) Machine learning-based dynamic model for on-site subcontractor performance management. Engineering, Construction and Architectural Management, 33(7), pp. 5592-5624. ISSN 0969-9988

Bhuiyan, S I; Jones, K and Wanigarathna, N (2015) An approach to sustainable refurbishment of existing building. In: Raiden, A and Aboagye-Nimo, E (eds.) Proceedings of 31st Annual ARCOM Conference, 7-9 September 2015, Lincoln, UK.

Birnie, J and Yates, A (1991) Cost prediction using decision/risk analysis methodologies. Construction Management and Economics, 9(2), pp. 171-186. ISSN 01446193

Bu-Qammaz, A S A S (2015) Risk management model for international public construction joint venture projects in Kuwait. PhD thesis, Ohio State University, USA.

Doczy, R (2018) Risk-benefit analysis and optimization of LEED-certified school buildings design and construction: Statisitical and machine learning approaches. PhD thesis, Florida State University, USA.

Doğan, S Z (2005) Using machine learning techniques for early cost prediction of structural systems of buildings. PhD thesis, Izmir Institute of Technology, Turkey.

Doǧan, S Z; Arditi, D and Murat Günaydin, H (2008) Using decision trees for determining attribute weights in a case-based model of early cost prediction. Journal of Construction Engineering and Management, 134(2), pp. 146-152. ISSN 0733-9364

Dreschler, M (2009) Fair competition: How to apply the 'economically most advantageous tender' award mechanism in the Dutch construction industry. PhD thesis, Delft University of Technology, Netherlands.

Esders, M C (2017) Consideration of uncertain future demand and decision flexibility in the determination of intervention programs for buildings. DSc thesis, ETH Zürich, Switzerland.

Fadiya, O; Georgakis, P; Chinyio, E and Nwagboso, C (2015) Decision-making framework for selecting ICT-based construction logistics systems. Journal of Engineering, Design and Technology, 13(2), pp. 260-281.

Fadiya, O O (2012) Development of an integrated decision analysis framework for selecting ICT-based logistics systems in the construction industry. PhD thesis, University of Wolverhampton, UK.

Goh, Y M and Binte Sa'Adon, N F (2015) Cognitive factors influencing safety behavior at height: A multimethod exploratory study. Journal of Construction Engineering and Management, 141(6): 04015003, ISSN 0733-9364

Gondia, A; Siam, A; El-Dakhakhni, W and Nassar, A H (2020) Machine learning algorithms for construction projects delay risk prediction. Journal of Construction Engineering and Management, 146(1): 04019085, ISSN 0733-9364

Gunduz, M and Al-Ajji, I (2022) Employment of CHAID and crt decision tree algorithms to develop bid/no-bid decision-making models for contractors. Engineering, Construction and Architectural Management, 29(9), pp. 3712-3736. ISSN 0969-9988

Gurmu, A and Miri, M P (2025) Machine learning regression for estimating the cost range of building projects. Construction Innovation, 25(2), pp. 577-593. ISSN 1471-4175

Haidar, A; Naoum, S; Howes, R and Tah, J (1999) Genetic algorithms application and testing for equipment selection. Journal of Construction Engineering and Management, 125(1), pp. 32-38. ISSN 0733-9364

Hajiashrafi, R (2025) Streamlined shapley value models for contribution-based compensation allocation in scheduling networks in construction project management. PhD thesis, Catholic University of America, USA.

Ihm, S Y; Lee, H J; Lee, E J and Park, Y H (2021) A policy knowledge- and reasoning-based method for data-analytic city policymaking. Building Research & Information, 49(1), pp. 38-54. ISSN 0961-3218

Javanmardi, A (2019) Strategies and predictive models for reducing workflow variability in construction production systems. PhD thesis, North Carolina State University, USA.

Jeljeli, M N (1994) A risk-based methodology for estimating contractors' liability in superfund cleanup construction. PhD thesis, University of Wisconsin - Madison, USA.

Jeljeli, M N and Russell, J S (1995) Coping with uncertainty in environmental construction: Decision-analysis approach. Journal of Construction Engineering and Management, 121(4), pp. 370-380. ISSN 0733-9364

Jeong, J and Jeong, J (2024) Sustainability in prefabricated construction: Enhancing multicriteria analysis and prediction using machine learning. Journal of Construction Engineering and Management, 150(8): 04024081, ISSN 0733-9364

Kalamaras, G S (1996) A case method approach for interactive risk analysis of tunnel "design-for-constructability" concept. PhD thesis, Pennsylvania State University, USA.

Kamal, P and Ahuja, S (2019) An ensemble-based model for prediction of academic performance of students in undergrad professional course. Journal of Engineering, Design and Technology, 17(4), pp. 769-781. ISSN 1726-0531

Kedarisetty, S (2025) Pavement management systems in local governments. PhD thesis, University of California, Davis, USA.

Kere, K J (2023) Probabilistic model development and risk management strategies for pipelines with anomalies. PhD thesis, Marquette University, USA.

Lewis, A (2013) A framework for improving building operations decisions for energy efficiency. PhD thesis, University of Reading, UK.

Lin, J; Xing, R and Cai, Y (2026) Advancing safer construction hris: A multisourced approach for diagnosing unsafe behavior tendencies. Journal of Construction Engineering and Management, 152(2): 04025247, ISSN 0733-9364

Macieira, M; Mendonça, P; Miranda Guedes, J and Tereso, A (2022) Evaluating the efficiency of membrane's refurbishment solutions to perform vertical extensions in old buildings using a multicriteria decision-support model. Architectural Engineering and Design Management, 18(1), pp. 1-25. ISSN 1745-2007

Mahfouz, T S (2009) Construction legal support for differing site conditions (DSC) through statistical modeling and machine learning (ML). PhD thesis, Iowa State University, USA.

Maloney, W F (1990) Framework for analysis of performance. Journal of Construction Engineering and Management, 116(3), pp. 399-415. ISSN 0733-9364

Mansoor, A; Liu, S; Bouferguene, A and Al-Hussein, M (2024) Crane signalman hand-signal classification framework using sensor-based smart construction glove and machine-learning algorithms. Journal of Construction Engineering and Management, 150(8): 04024094, ISSN 0733-9364

Marzouk, M and Moamen, M (2009) A framework for estimating negotiation amounts in construction projects. Construction Innovation, 9(2), pp. 133-148. ISSN 1471-4175

Mohamed, S Y (2020) Stochastic performance and maintenance optimization models for pavement infrastructure management. PhD thesis, Purdue University, USA.

Mohammed, A; Bahatheq, A; Ghaithan, A; Alshibani, A; Mazher, K M and Alrashidi, A (2026) Predicting schedule delays of construction projects in the oil and gas industry: Comparative study. Built Environment Project and Asset Management, 16(2), pp. 286-303. ISSN 2044-124X

Moussa, M; Ruwanpura, J and Jergeas, G (2006) Decision tree modeling using integrated multilevel stochastic networks. Journal of Construction Engineering and Management, 132(12), pp. 1254-1266. ISSN 0733-9364

Moussa, M; Ruwanpura, J and Jergeas, G (2007) CTAN for risk assessments using multilevel stochastic networks. Journal of Construction Engineering and Management, 133(1), pp. 96-101. ISSN 0733-9364

Naumets, S and Lu, M (2021) Investigation into explainable regression trees for construction engineering applications. Journal of Construction Engineering and Management, 147(8), ISSN 0733-9364

Nyakaana Blair, A M A (1999) Risk analysis of cost and schedule of complex engineering systems. PhD thesis, University of Maryland, College Park, USA.

Ortiz, S S (2025) Strengthening construction supply chains: An exploration of decision-making frameworks for resilience in the face of black swan event. PhD thesis, Purdue University, Indiana, USA.

Pan, L-J (1996) A study of risk management in dealing with contracts in the construction industry. PhD thesis, University of Glasgow, UK.

Prinsloo, H F (2016) Toward a decision framework for the analysis of construction claims. PhD thesis, University of Pretoria, South Africa.

Pulket, T and Arditi, D (2009) Construction litigation prediction system using ant colony optimization. Construction Management and Economics, 27(3), pp. 241-251. ISSN 1466433X

Qiao, J; Wang, C; Guan, S and Shuran, L (2022) Construction-accident narrative classification using shallow and deep learning. Journal of Construction Engineering and Management, 148(9): 04022088, ISSN 0733-9364

Rai, H; Jagannathan, M and Venkata Santosh Kumar, D (2021) Claim tenability assessment in Indian real estate projects using ann and decision tree models. Built Environment Project and Asset Management, 11(3), pp. 468-487. ISSN 2044-124X

Ryu, J; Seo, J; Jebelli, H and Lee, S (2019) Automated action recognition using an accelerometer-embedded wristband-type activity tracker. Journal of Construction Engineering and Management, 145(1): 04018114, ISSN 0733-9364

Salvado, F; Almeida, N and Vale e Azevedo, A (2020) Aligning financial and functional equivalent depreciations rates of building assets. Engineering, Construction and Architectural Management, 27(2), pp. 441-457. ISSN 0969-9988

Shafaat, A (2016) Designing project systems in presence of variations. PhD thesis, Purdue University, USA.

Shahedi, F; Etemadfard, H; Omrani, F and Ghalehnovi, M (2024) Cost performance modeling for steel fabrication shops with machine learning algorithms. Journal of Construction Engineering and Management, 150(9): 04024114, ISSN 0733-9364

Shayboun, M; Kifokeris, D and Koch, C (2020) Machine learning for analysis of occupational accidents registration data. In: Scott, L and Neilson, C J (eds.) Proceedings of 36th Annual ARCOM Conference, 7-8 September 2020, Online Event, UK.

Shayboun, M; Koch, C and Kifokeris, D (2021) A comparison of accident causation models (ACMS) and machine learning (ML) for applied analysis within accident reports. In: Scott, L and Neilson, C J (eds.) Proceedings of 37th Annual ARCOM Conference, 6-7 September 2021, Online Event, UK.

Staneff, S T (1997) A decision support system for infrastructure management. PhD thesis, University of California, Berkeley, USA.

Syachrani, S (2010) Advanced sewer asset management using dynamic deterioration models. PhD thesis, Oklahoma State University, USA.

Thach, H. P.; Nguyen, L. D. and Nguyen, V. T. (2026) Integrating coastal segmentation on predictive modeling for data-driven bridge asset management. International Journal of Construction Management, 26(10), pp. 2228-2244. ISSN 1562-3599

Toma, H M; Abdeen, A H and Ibrahim, A (2025) Predicting construction equipment resale price: Machine learning model. Engineering, Construction and Architectural Management, 32(5), pp. 3453-3464. ISSN 0969-9988

Wee, S (1993) A prototype of an expert system for pavement maintenance and rehabilitation strategy in the state of Ohio (espresso). PhD thesis, Ohio State University, USA.

Wood, G and Ellis, R (2001) An exploration of approaches to risk management applications within UK construction projects. In: Akintoye, A (ed.) Proceedings of 17th Annual ARCOM Conference, 5-7 September 2001, Salford, UK.

Wusu, G E; Alaka, H; Yusuf, W; Mporas, I; Toriola-Coker, L and Oseghale, R (2024) A machine learning approach for predicting critical factors determining adoption of offsite construction in Nigeria. Smart and Sustainable Built Environment, 13(6), pp. 1408-1433. ISSN 2046-6099

Xie, H; Hong, Y and Brilakis, I (2022) Analysis of user needs in time-related risk management for holistic project understanding. Journal of Construction Engineering and Management, 148(4): 05022002, ISSN 0733-9364

Xie, L L; Chen, Y; Wu, S; Chang, R D and Han, Y (2024) Knowledge extraction for solving resource-constrained project scheduling problem through decision tree. Engineering, Construction and Architectural Management, 31(7), pp. 2852-2877. ISSN 0969-9988

Ye, S and Liu, Y (2008) Study on development patterns of infrastructure projects. Journal of Construction Engineering and Management, 134(2), pp. 94-102. ISSN 0733-9364

You, X (2010) Risk analysis in tunneling with imprecise probabilities. PhD thesis, University of Texas at Austin, USA.

Zara, R B; Moro, G N; Martins, R d S V and Giglio, T G F (2025) Application of a decision tree approach to predict energy consumption in lightweight buildings under subtropical climate. Smart and Sustainable Built Environment, 14(7), pp. 2069-2089. ISSN 2046-6099

Zeng, S; Chung, F and Ashuri, B (2024) Forecasting right-of-way (ROW) acquisition timeline of transportation projects. Built Environment Project and Asset Management, 14(2), pp. 129-146. ISSN 2044-124X

Zhang, F (2022) A hybrid structured deep neural network with word2vec for construction accident causes classification. International Journal of Construction Management, 22(6), pp. 1120-1140. ISSN 1562-3599

Zhang, Z; Koh, Z Y and Ling, F (2020) Benchmarking contractors' financial performance: Case study of Singapore. Journal of Financial Management of Property and Construction, 25(2), pp. 183-199. ISSN 1366-4387

du Toit, J and Wagner, C (2020) The effect of housing type on householders' self-reported participation in recycling. Smart and Sustainable Built Environment, 9(4), pp. 395-412. ISSN 2046-6099

van den Boomen, M; Spaan, M T J; Schoenmaker, R and Wolfert, A R M (2019) Untangling decision tree and real options analyses: A public infrastructure case study dealing with political decisions, structural integrity and price uncertainty. Construction Management and Economics, 37(1), pp. 24-43. ISSN 01446193