Items with Subject: artificial intelligence

A. Mohy, A.; Bassioni, H. A.; Elgendi, E. O. and Hassan, T. M. (2026) Modeling spatiotemporal hazard dynamics for construction safety using graph attention networks. Journal of Engineering, Design and Technology, ISSN 1726-0531

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

Abbasnejad, B; Nasirian, A; Duan, S; Diro, A; Prasad Nepal, M and Song, Y (2024) Measuring BIM implementation: A mathematical modeling and artificial neural network approach. Journal of Construction Engineering and Management, 150(5): 04024032, ISSN 0733-9364

AbdElMottaleb, Mohamed (2025) AI in project management: Machine learning application for construction scheduling. PhD thesis, University of Salford, UK.

Abdel-Galil, E; Ibrahim, A H and Alborkan, A (2022) Assessment of transaction costs for construction projects. International Journal of Construction Management, 22(9), pp. 1618-1631. ISSN 1562-3599

AbdelRazig, Y A (1999) Construction quality assessment: A hybrid decision support model using image processing and neural learning for intelligent defects recognition. PhD thesis, Purdue University, USA.

AbdelRazig, Y A and Chang, L M (2000) Intelligent model for constructed facilities surface assessment. Journal of Construction Engineering and Management, 126(6), pp. 422-432. ISSN 0733-9364

Abdelkader, E M; Moselhi, O; Marzouk, M and Zayed, T (2021) Integrative evolutionary-based method for modeling and optimizing budget assignment of bridge maintenance priorities. Journal of Construction Engineering and Management, 147(9): 04021100, ISSN 0733-9364

Abdelmassih, A; Faddoul, R and Geara, F (2023) Impact of autonomous solutions on earthmoving electrification using machine learning: Case study. Construction Innovation, 23(3), pp. 606-621. ISSN 1471-4175

Abdou, A; Lewis, J and Alzarooni, S (2004) Modelling risk for construction cost estimating and forecasting: A review. In: Khosrowshahi, F (ed.) Proceedings of 20th Annual ARCOM Conference, 1-3 September 2004, Edinburgh, UK.

AbouRizk, S M and Wales, R J (1997) Combined discrete-event/continuous simulation for project planning. Journal of Construction Engineering and Management, 123(1), pp. 11-20. ISSN 0733-9364

Abounia Omran, B (2016) Application of data mining and big data analytics in the construction industry. PhD thesis, Ohio State University, USA.

Abruzzini, A and Abrishami, S (2022) Integration of BIM and advanced digital technologies to the end of life decision-making process: A paradigm of future opportunities. Journal of Engineering, Design and Technology, 20(2), pp. 388-413. ISSN 1726-0531

Abu Dabous, S; Ibrahim, F and Alzghoul, A (2025) Modelling bridge deterioration using long short-term memory neural networks: A deep learning-based approach. Smart and Sustainable Built Environment, 14(5), pp. 1632-1655. ISSN 2046-6099

Abu Dabous, S; Alzghoul, A and Ibrahim, F (2025) Intelligent condition prediction model for bridge infrastructure based on evaluating machine learning algorithms. Smart and Sustainable Built Environment, 14(2), pp. 557-576. ISSN 2046-6099

Abu-Mahfouz, E; Al-Dahidi, S; Gharaibeh, E and Alahmer, A (2025) A novel feature engineering-based hybrid approach for precise construction cost estimation using fuzzy-AHP and artificial neural networks. International Journal of Construction Management, 25(15), pp. 1800-1810. ISSN 1562-3599

Abuhishmeh, K S K (2023) Risk assessment of reinforced concrete sewer pipes under external loading and adverse environmental conditions using an adaptive neuro-fuzzy system. PhD thesis, University of Texas at Arlington, USA.

Abusnina, H (2019) Combining engineering and data-driven approaches to model the risk of excavation damage to underground natural gas facilities. PhD thesis, Rutgers The State University of New Jersey, School of Graduate Studies, USA.

Acheamfour, V K; Adjei-Kumi, T and Kissi, E (2023) Contractor selection: A review of qualification and pre-qualification systems. International Journal of Construction Management, 23(2), pp. 338-348. ISSN 1562-3599

Acheampong, A; Adjei, E K; Asiedu, R O; Atibila, D W and Abu, I M A (2025) Evaluating the factors influencing artificial intelligence technology uptake in health and safety management within the Ghanaian construction industry. Journal of Engineering, Design and Technology, 23(6), pp. 2060-2081. ISSN 1726-0531

Adamu, I I; Okanlawon, T T; Oyewobi, L O; Shittu, A A and Jimoh, R A (2026) Revolutionising construction safety: Benefits of harnessing artificial intelligence tools for dynamic monitoring of safety compliance on construction projects in Nigeria. International Journal of Building Pathology and Adaptation, 44(1), pp. 241-265. ISSN 2398-4708

Adedokun, O; Egbelakin, T and Omotayo, T (2024) Random forest and path diagram taxonomies of risks influencing higher education construction projects. International Journal of Construction Management, 24(1), pp. 66-74. ISSN 1562-3599

Adeli, H and Wu, M (1998) Regularization neural network for construction cost estimation. Journal of Construction Engineering and Management, 124(1), pp. 18-23. ISSN 0733-9364

Adeosun, F E and Oke, A E (2024) Examining the awareness and usage of cyber physical systems for construction projects in Nigeria. Journal of Engineering, Design and Technology, 22(1), pp. 281-294. ISSN 1726-0531

Adesina, Adebola (2025) Examining influential factors on the success of project management in education: A content analysis. EdD thesis, University of Nevada, Reno, USA.

Adinyira, E; Adjei, E A G; Agyekum, K and Fugar, F D K (2021) Application of machine learning in predicting construction project profit in Ghana using support vector regression algorithm (svra). Engineering, Construction and Architectural Management, 28(5), pp. 1491-1514. ISSN 0969-9988

Adio, Obafemi Adekunle (2022) An automated knowledge-based decision support system for managing non-conformances on australia's large infrastructure projects. PhD thesis, University of Melbourne, Australia.

Adu-Gyamfi, B; Ariyaningsih, A; Zuquan, H; Yamazawa, N; Kato, A and Shaw, R (2024) Reflections on science, technology and innovation on the aspirations of the Sendai framework for disaster risk reduction. International Journal of Disaster Resilience in the Built Environment, 15(2), pp. 289-302. ISSN 1759-5916

Adul-Hamid, R (1996) Construction duration prediction using neural network methodology. PhD thesis, University of Manchester, UK.

Afzal, Muneeb (2024) Improving request for information (RFI) processing in construction projects using natural language processing (NLP) techniques. PhD thesis, University of Technology Sydney, Australia.

Agapaki, E and Brilakis, I (2021) Cloi: An automated benchmark framework for generating geometric digital twins of industrial facilities. Journal of Construction Engineering and Management, 147(11): 04021145, ISSN 0733-9364

Aghili, S. A.; Khanzadi, M.; Haji Mohammad Rezaei, A. and Rahbar, M. (2026) Data-driven approach to fault detection for hospital HVAC system. Smart and Sustainable Built Environment, 15(2), pp. 765-788. ISSN 2046-6099

Aghimien, D; Aghimien, E I; Aigbavboa, C O; Aliu, J O; Oke, A E and Chan, D W M (2026) Strategies for enhancing construction digitalisation: A machine learning-based sensitivity analysis. Engineering, Construction and Architectural Management, 33(15), pp. 115-136. ISSN 0969-9988

Aghimien, D; Aigbavboa, C O; Chan, D W M and Aghimien, E I (2024) Determinants of cloud computing deployment in South African construction organisations using structural equation modelling and machine learning technique. Engineering, Construction and Architectural Management, 31(3), pp. 1037-1060. ISSN 0969-9988

Agri, M. E.; Le, A. and Phung, Q. (2026) AI integration in architectural design and management: Professionals' perspectives. Architectural Engineering and Design Management, 22(1), pp. 67-82. ISSN 1745-2007

Ahiaga-Dagbui, D and Smith, S D (2012) Neural networks for modelling the final target cost of water projects. In: Smith, S D (ed.) Proceedings of 28th Annual ARCOM Conference, 3-5 September 2012, Edinburgh, UK.

Ahiaga-Dagbui, D D (2014) Rethinking construction cost overruns: an artificial neural network approach to construction cost estimation. PhD thesis, University of Edinburgh, UK.

Ahiaga-Dagbui D D, T O and Smith S D, W S (2013) A neuro-fuzzy hybrid model for predicting final cost of water infrastructure projects. In: Smith, S D and Ahiaga-Dagbui, D D (eds.) Proceedings of 29th Annual ARCOM Conference, 2-4 September 2013, Reading, UK.

Ahmed, M O; Khalef, R; Ali, G G and El-Adaway, I H (2021) Evaluating deterioration of tunnels using computational machine learning algorithms. Journal of Construction Engineering and Management, 147(10): 04021125, ISSN 0733-9364

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.

Ahn, Sang Jun (2019) Transportation framework in panelized construction for residential building. PhD thesis, University of Alberta, Canada.

Aibinu, A A; Dassanayake, D; Chan, T-K and Thangaraj, R (2015) Cost estimation for electric light and power elements during building design: A neural network approach. Engineering, Construction and Architectural Management, 22(2), pp. 190-213. ISSN 0969-9988

Ainoo, F N Y (2025) Leveraging big data in AEC decision-making: A governance framework. PhD thesis, Capella University, USA.

Aiolova, Maria (2026) Building AI fluency in the built environment: Developing organizational learning cultures to drive AI adoption and innovation in the architecture, engineering, and construction industry. EdD thesis, Northeastern University, USA.

Ajani, A A and Olapade, D T (2025) Building design considerations for healthy and active aging-in-place. International Journal of Building Pathology and Adaptation, 43(6), pp. 1466-1481. ISSN 2398-4708

Akhavian, Reza (2015) Data-driven simulation modeling of construction and infrastructure operations using process knowledge discovery. PhD thesis, University of Central Florida, USA.

Akinade, O O (2017) BIM-based software for construction waste analytics using artificial intelligence hybrid models. PhD thesis, University of the West of England, Bristol, UK.

Akinsola, A O (1997) An intelligent model of variations' contingency on constructions projects. PhD thesis, University of Wolverhampton, UK.

Akomea-Frimpong, I; Dzagli, J R A D; Eluerkeh, K; Bonsu, F B; Opoku-Brafi, S; Gyimah, S; Asuming, N A S; Atibila, D W and Kukah, A S (2025) A systematic review of artificial intelligence in managing climate risks of PPP infrastructure projects. Engineering, Construction and Architectural Management, 32(4), pp. 2430-2454. ISSN 0969-9988

Al Bunni, A (2020) Refurbishment of UK state school buildings: a strategy and framework for BIM-based digital twinning. PhD thesis, De Montfort University, UK.

Al Dairi, J S S (2017) The design and development of a knowledge-based lean six sigma maintenance system for sustainable buildings. PhD thesis, University of Bradford, UK.

Al Jassmi, H; Al Ahmad, M and Ahmed, S (2021) Automatic recognition of labor activity: A machine learning approach to capture activity physiological patterns using wearable sensors. Construction Innovation, 21(4), pp. 555-575. ISSN 1471-4175

Al Omari, Mohammad K (2025) Application of the AI-enabled unmanned aerial systems in resolving highway construction claims. PhD thesis, University of Illinois at Chicago, 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

Al-Bizri, S (1995) Design management plan generator, knowledge-based system for planning the design processes in the construction industry. PhD thesis, University of Reading, UK.

Al-Ghassani, A M; Kamara, J M; Anumba, C J and Carrillo, P M (2006) Prototype system for knowledge problem definition. Journal of Construction Engineering and Management, 132(5), pp. 516-524. ISSN 0733-9364

Al-Hadidi, S; Sweis, G; Abu-Khader, W; Abu-Rumman, G and Sweis, R (2024) Managing future urbanization growth patterns using genetic algorithm modeling. Engineering, Construction and Architectural Management, 31(7), pp. 2648-2668. ISSN 0969-9988

Al-Otaibi, N T N H (1995) A knowledge-based systems approach to materials management for large construction projects. PhD thesis, University of Toronto, Canada.

Al-Sobiei, O S (2001) Assessment of risk allocation in construction projects. PhD thesis, Illinois Institute of Technology, USA.

Al-Tabtabai, H and Alex, A P (1999) Using genetic algorithms to solve optimization problems in construction. Engineering, Construction and Architectural Management, 6(2), pp. 121-132. ISSN 0969-9988

Al-Tabtabai, H; Kartam, N; Flood, I A N and Alex, A P (1997) Expert judgment in forecasting construction project completion. Engineering, Construction and Architectural Management, 4(4), pp. 271-293. ISSN 0969-9988

Al-Tabtabai, H M (1989) PROCON: A knowledge-based approach to construction project control. PhD thesis, University of Colorado at Boulder, USA.

Al-Zahrani, J I (2013) The impact of contractors' attributes on construction project success. PhD thesis, University of Manchester, UK.

AlTalhoni, A; Alwashah, Z; Liu, H; Abudayyeh, O; Kwigizile, V and Kirkpatrick, K (2026) Data-driven identification of key pricing factors in highway construction cost estimation during economic volatility. International Journal of Construction Management, 26(1), pp. 152-167. ISSN 1562-3599

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

Aldaghi, T and Javanmard, S (2023) The evaluation of wastewater treatment plant performance: A data mining approach. Journal of Engineering, Design and Technology, 21(6), pp. 1785-1802. ISSN 1726-0531

Alex, D P; Al Hussein, M; Bouferguene, A and Fernando, S (2010) Artificial neural network model for cost estimation: City of Edmonton's water and sewer installation services. Journal of Construction Engineering and Management, 136(7), pp. 745-756. ISSN 0733-9364

Algarni, S K (2022) Machine learning for improved detection and segmentation of building boundary. PhD thesis, Cardiff University, UK.

Alharbi, E A and Alsehaimi, A (2025) Machine learning model to predict the cooling load of mosque buildings during the design stage. International Journal of Construction Management, 25(8), pp. 965-979. ISSN 1562-3599

Alhosani, Y (2017) An empirical investigation of the demographics of top management team (TMT) and its influence in forecasting organizational outcome in international architecture, engineering and construction (AEC) firms: A fuzzy set approach. DEng thesis, Ecole de Technologie Superieure, Canada.

Ali, A.; Zhifeng, S.; Tahir, M.; Ye, Y.; Wang, G.; Wei, X. and Zang, X. (2026) Enhancing megaproject performance by integrating artificial intelligence, human-robot collaboration, and BIM-integration management: The moderating role of top management support. Journal of Construction Engineering and Management, 152(7): 04026094, ISSN 0733-9364

Ali, B; Aibinu, A A and Paton-Cole, V (2024) Closing the information gaps: A systematic review of research on delay and disruption claims. Construction Innovation, 24(3), pp. 790-810. ISSN 1471-4175

Aliasgari, R; Fan, C; Li, X; Golabchi, A and Hamzeh, F (2024) MOCAP and ai-based automated physical demand analysis for workplace safety. Journal of Construction Engineering and Management, 150(7): 04024060, ISSN 0733-9364

Alikhani, H; Le, C; Jeong, H D and Damnjanovic, I (2023) Sequential machine learning for activity sequence prediction from daily work report data. Journal of Construction Engineering and Management, 149(9): 04023082, ISSN 0733-9364

Alipouri, Y; Bokharaeian, A and Monfared, E (2025) Construction labor activity recognition via an imu-implemented wristband. Journal of Construction Engineering and Management, 151(11): 04025182, ISSN 0733-9364

Aljagoub, D (2025) Enhancing delamination detection and monitoring of concrete bridges through infrared thermography, deep learning, field data, and numerical simulations. PhD thesis, University of Delaware, USA.

Alkaissy, Maryam (2022) Worksite accidents quantification in construction: Safety relations with project performance metrics. PhD thesis, Monash University, Australia.

Alkass, S and Harris, F (1988) Expert system for earthmoving equipment selection in road construction. Journal of Construction Engineering and Management, 114(3), pp. 426-440. ISSN 0733-9364

Alkoc, E and Erbatur, F (1998) Site expert: A prototype knowledge-based expert system. Engineering, Construction and Architectural Management, 5(3), pp. 238-251. ISSN 0969-9988

Almatared, M M S (2024) An integrated digital twin framework and evacuation simulation system for enhanced safety in smart buildings. PhD thesis, Western Michigan University, USA.

Alnaqbi, A; Al-Khateeb, G G and Zeiada, W (2025) Machine learning applications for predicting longitudinal cracking in continuously reinforced concrete pavement. Construction Economics and Building, 25(1), pp. 143-170. ISSN 2204-9029

Alqady, M (2012) Leveraging text content for management of construction project documents. PhD thesis, Purdue University, USA.

Alqahtani, A and Whyte, A (2013) Artificial neural networks incorporating cost significant items towards enhancing estimation for (life-cycle) costing of construction projects. Construction Economics and Building, 13(3), pp. 51-64. ISSN 2204-9029

Alshawi, M and Hassan, Z (1999) Integrated models for construction planning: Object flow and relationship. Engineering, Construction and Architectural Management, 6(2), pp. 197-212. ISSN 0969-9988

Alshboul, O and Shehadeh, A (2026) Adaptive integration of BIM and Navisworks for real-time clash detection using the XGBoost algorithm. Journal of Construction Engineering and Management, 152(1): 04025232, ISSN 0733-9364

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

Alshboul, O; Shehadeh, A and Tamimi, M (2025) Sustainability-focused pavement management under climate variability. Journal of Construction Engineering and Management, 151(7): 04025076, ISSN 0733-9364

Alsubaey, M H (2017) A hybrid machine learning and text-mining approach for the automated generation of early warnings in construction project management. PhD thesis, Cranfield University, UK.

Alsugair, A M (1992) An intelligent resource allocation system. PhD thesis, Texas A&M University, USA.

Altalhoni, A; Liu, H; Abudayyeh, O; Kwigizile, V; Huang, W C and Kirkpatrick, K (2025) Robust forecasting models for highway construction cost indices during pandemic-era inflation. Journal of Construction Engineering and Management, 151(8): 04025101, ISSN 0733-9364

Altawil, Shadi N A (2017) Multi-level knowledge extraction and modeling to support job hazard analysis process for oil and gas pipeline projects. PhD thesis, University of Alberta, Canada.

Altay, B and Salcı, E (2024) Exploring designers' finishing materials selection for residential interior spaces. Architectural Engineering and Design Management, 20(2), pp. 269-286. ISSN 1745-2007

Altun, M (2024) Data-driven and knowledge-assisted model-based frameworks for supporting facility maintenance. PhD thesis, Middle East Technical University, Turkey.

Aluko, R O; Adenuga, O A; Kukoyi, P O; Soyingbe, A A and Oyedeji, J O (2016) Predicting the academic success of architecture students by pre-enrolment requirement: Using machine-learning techniques. Construction Economics and Building, 16(4), pp. 86-98. ISSN 2204-9029

Aluko, R O; Daniel, E I; Shamsideen Oshodi, O; Aigbavboa, C O and Abisuga, A O (2018) Towards reliable prediction of academic performance of architecture students using data mining techniques. Journal of Engineering, Design and Technology, 16(3), pp. 385-397. ISSN 1726-0531

Alves, J. L.; Almeida Filho, A. T. D.; Bradaschia, F. and Palha, R. P. (2026) Solarisbim.AI: Smart sustainable building planning with BIM-based solar-production estimation using machine-learning radiation forecasts. Journal of Construction Engineering and Management, 152(6): 04026076, ISSN 0733-9364

Alyileili, M and Opoku, A (2025) Artificial intelligence ethics in municipal and construction sectors: A literature review. Construction Economics and Building, 25(3-4), pp. 210-230. ISSN 2204-9029

Alzubi, K. M.; Alaloul, W. S.; Al Salaheen, M.; Musarat, M. A.; Baarimah, A. O. and Mushtaha, A. W. (2025) Indoor construction productivity assessment using computer vision and mask region-based convolutional neural networks. Construction Innovation, 26(5), pp. 1523-1555. ISSN 1471-4175

Alzubi, Y; Aljaafreh, A and Khatatbeh, A (2024) Application of machine learning techniques in estimating the construction cost of residential buildings in the middle East region. International Journal of Construction Management, 24(9), pp. 946-958. ISSN 1562-3599

Amer, F; Koh, H Y and Golparvar-Fard, M (2021) Automated methods and systems for construction planning and scheduling: Critical review of three decades of research. Journal of Construction Engineering and Management, 147(7): 0002093, ISSN 0733-9364

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

Andersen, T O M and Gaarslev, A (1996) Perspectives on artificial intelligence in the construction industry. Engineering, Construction and Architectural Management, 3(1-2), pp. 3-14. ISSN 0969-9988

Antwi-Afari, M F; Li, H; Umer, W; Yu, Y and Xing, X (2020) Construction activity recognition and ergonomic risk assessment using a wearable insole pressure system. Journal of Construction Engineering and Management, 146(7): 04020077, ISSN 0733-9364

Anwar, Waqas (2019) Development of multiple linear regression model and rule based decision support system to improve supply chain management of road construction projects in disaster regions. PhD thesis, University of Bradford, UK.

Anwer, S; Li, H; Umer, W; Antwi-Afari, M F; Mehmood, I; Yu, Y; Haas, C and Wong, A Y L (2023) Identification and classification of physical fatigue in construction workers using linear and nonlinear heart rate variability measurements. Journal of Construction Engineering and Management, 149(7): 04023057, ISSN 0733-9364

Arain, F M (2009) Leveraging on information technology to teach construction law to built environment students: A knowledge-based system approach. Journal of Construction in Developing Countries, 14(2), pp. 77-102. ISSN 1823-6499

Arakawa Martins, L; Soebarto, V; Williamson, T and Pisaniello, D (2022) Personal thermal comfort models: A deep learning approach for predicting older people's thermal preference. Smart and Sustainable Built Environment, 11(2), pp. 245-270. ISSN 2046-6099

Arida, M A (2024) Enhancing thermal comfort in commercial buildings: Contributions of machine learning algorithms for optimizing predictive thermal comfort indices. PhD thesis, North Carolina Agricultural and Technical State University, USA.

Art Chaovalitwongse, W; Wang, W; Williams, T P and Chaovalitwongse, P (2012) Data mining framework to optimize the bid selection policy for competitively bid highway construction projects. Journal of Construction Engineering and Management, 138(2), pp. 277-286. ISSN 0733-9364

Asare, O; Obi, L and Thurairajah, N (2024) Leveraging circular economy applications in the offsite construction sector through artificial intelligence: A scientometric review. In: Thomson, C (ed.) Proceedings of 40th Annual ARCOM Conference, 2-4 September 2024, London South Bank University, UK.

Asghari, V and Hsu, S C (2022) Upscaling complex project-level infrastructure intervention planning to network assets. Journal of Construction Engineering and Management, 148(1): 04021188, ISSN 0733-9364

Ashtab, M and Ryoo, B Y (2022) Predicting construction workforce demand using a combination of feature selection and multivariate deep-learning seq2seq models. Journal of Construction Engineering and Management, 148(12): 04022136, ISSN 0733-9364

Assaf, G and Assaad, R H (2024) A data-driven decision-support tool for selecting the optimal project delivery method for bundled projects: Integrating machine learning and expert domain knowledge. Journal of Construction Engineering and Management, 150(12): 04024181, ISSN 0733-9364

Atkin, B and Bildsten, L (2017) A future for facility management. Construction Innovation, 17(2), pp. 116-124. ISSN 1471-4175

Attalla, M M A M (2000) Reconstruction of operating facilities: A model for project management. PhD thesis, University of Waterloo, Canada.

Atuahene, B T; Kanjanabootra, S and Gajendra, T (2020) Benefits of big data application experienced in the construction industry: A case of an Australian construction company. In: Scott, L and Neilson, C J (eds.) Proceedings of 36th Annual ARCOM Conference, 7-8 September 2020, Online Event, UK.

Auchey, F L and Auchey, G J (2004) Picking successful projects by using the prism lltm model. In: Khosrowshahi, F (ed.) Proceedings of 20th Annual ARCOM Conference, 1-3 September 2004, Edinburgh, UK.

Avci, A B (2026) Machine learning-based prediction of thermal comfort: Exploring building types, climate, ventilation strategies, and seasonal variations. Building Research & Information, 54(1), pp. 100-117. ISSN 0961-3218

Awad, A and Fayek, A R (2013) Adaptive learning of contractor default prediction model for surety bonding. Journal of Construction Engineering and Management, 139(6), pp. 694-704. ISSN 0733-9364

Awad, A L S (2012) Intelligent contractor default prediction model for surety bonding in the construction industry. PhD thesis, University of Alberta, Canada.

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

Ayat, M; Ullah, M; Pervez, Z; Lawrence, J; Kang, C W and Ullah, A (2025) Analyzing the differential impact of variables on the success of solicited and unsolicited private participation in infrastructure projects using machine learning techniques. Engineering, Construction and Architectural Management, 32(12), pp. 7909-7937. ISSN 0969-9988

Aydin, Y C and Mirzaei, P A (2022) A novel mathematical model to measure individuals' perception of the symmetry level of building facades. Architectural Engineering and Design Management, 18(3), pp. 261-278. ISSN 1745-2007

Aydinli, S (2024) Impact of unexpected conditions on construction cost forecasting performance: evidence from Europe. Construction Management and Economics, 42(9), pp. 787-801. ISSN 01446193

Ayhan, M (2019) Development of dispute prediction and resolution method selection models for construction disputes. PhD thesis, Middle East Technical University, Turkey.

Ayhan, M; Dikmen, I and Talat Birgonul, M (2021) Predicting the occurrence of construction disputes using machine learning techniques. Journal of Construction Engineering and Management, 147(4): 04021022, ISSN 0733-9364

Ayinla, K; Saka, A; Seidu, R and Madanayake, U (2023) The impact of artificial intelligence on construction costing practice. In: Tutesigensi, A and Neilson, C J (eds.) Proceedings of 39th Annual ARCOM Conference, 4-6 September 2023, University of Leeds, Leeds, UK.

Ayoubi, M. and Arashpour, M. (2026) Early recognition of workplace hazards using data-efficient multimodal learnable prompting and parameter-efficient fine tuning. Journal of Construction Engineering and Management, 152(10): 04026165, ISSN 0733-9364

Ayoubi, M. and Arashpour, M. (2026) Early recognition of workplace hazards using data-efficient multimodal learnable prompting and parameter-efficient fine tuning. Journal of Construction Engineering and Management, 152(10): 04026165, ISSN 0733-9364

Ağar, M (2024) A rule based expert system for delay analysis in construction projects. PhD thesis, Middle East Technical University, Turkey.

Badawy, M; Hussein, A; Elseufy, S M and Alnaas, K (2021) How to predict the rebar labours' production rate by using ANN model. International Journal of Construction Management, 21(4), pp. 427-438. ISSN 1562-3599

Badi, S.; Suliman, A.; Torku, A. and Yasin, K. (2026) How does AI adoption in construction organisations influence employee well-being? The mediating role of job crafting. Construction Management and Economics, 44(8), pp. 613-638. ISSN 0144-6193

Bae, J (2025) Supervised learning to covering cost risk through post-construction evaluation of transportation projects by project delivery methods. Engineering, Construction and Architectural Management, 32(9), pp. 5863-5884. ISSN 0969-9988

Bai, S; Li, M; Lu, Q; Tian, H and Qin, L (2022) Global time optimization method for dredging construction cycles of trailing suction hopper dredger based on grey system model. Journal of Construction Engineering and Management, 148(2): 04021198, ISSN 0733-9364

Baker, H (2021) A multimethod approach to learning from text-based construction failure data. PhD thesis, University of Edinburgh, UK.

Baker, H; Smith, S; Masterton, G and Hewlett, B (2020) Data-led learning: Using natural language processing (NLP) and machine learning to learn from construction site safety failures. In: Scott, L and Neilson, C J (eds.) Proceedings of 36th Annual ARCOM Conference, 7-8 September 2020, Online Event, UK.

Bakheet, M T (1995) Contractors' risk assessment system. PhD thesis, Georgia Institute of Technology, USA.

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