Items with Index Term: forest

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

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

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

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

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

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.

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

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

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

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

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

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

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

Ayat, M; Kim, B and Kang, C W (2023) A new data mining-based framework to predict the success of private participation in infrastructure projects. International Journal of Construction Management, 23(13), pp. 2151-2159. ISSN 1562-3599

Aye, L; Bamford, N; Charters, B and Robinson, J (2002) The carbon footprint of a new commercial building. In: Greenwood, D (ed.) Proceedings of 18th Annual ARCOM Conference, 2-4 September 2002, Northumbria, UK.

Bortey, L; Edwards, D J; Roberts, C and Rillie, I (2025) Unravelling incipient accidents: A machine learning prediction of incident risks in highway operations. Smart and Sustainable Built Environment, 14(6), pp. 1991-2022. ISSN 2046-6099

Bowers, C T (2019) The next generation of residential construction: Adoption of green building programs, environmentally certified wood products and the transparency of environmental friendliness. PhD thesis, University of Washington, USA.

Campo, S (2002) Asymmetry and risk aversion in first -price sealed bid auctions: Identification, estimation, and applications. PhD thesis, University of Southern California, USA.

Chen, H; Feng, Z; Liu, Y; Chen, B; Deng, T; Qin, Y and Xu, W (2023) Multiobjective optimization of a 3D laser scanning scheme for engineering structures based on rf-NSGA-II. Journal of Construction Engineering and Management, 149(2): 4022169, ISSN 0733-9364

Deng, S; Ni, P; Zhu, H; Cai, Y and Pan, Y (2024) Artificial cognition to predict and explain the potential unsafe behaviors of construction workers. Journal of Construction Engineering and Management, 150(7): 04024074, ISSN 0733-9364

Dick, B M (2019) Diagnostic testing in the natural and built environment. PhD thesis, North Carolina State University, USA.

Dinesh, C P; Bari, A U; Dissanayake, R P G and Tamura, M (2013) Detecting and assessment of tsunami building damage using high-resolution satellite images with GIS data. International Journal of Disaster Resilience in the Built Environment, 4(2), pp. 132-144. ISSN 1759-5916

Duan, P; Zhou, J and Tao, S (2023) Risk events recognition using smartphone and machine learning in construction workers' material handling tasks. Engineering, Construction and Architectural Management, 30(8), pp. 3562-3582. ISSN 0969-9988

ElAlem, M A; Mahdi, I M; Mohamadien, H A and Hosny, S (2025) Forecasting scope creep in Egyptian construction projects: An evaluation using artificial neural network (ANN) and random forest models. International Journal of Construction Management, 25(16), pp. 2082-2101. ISSN 1562-3599

Elmousalami, H H (2020) Artificial intelligence and parametric construction cost estimate modeling: State-of-the-art review. Journal of Construction Engineering and Management, 146(1): 03119008, ISSN 0733-9364

Elsherbiny, A (2021) Prediction of design error rework cost in EPC industrial projects. DEng thesis, George Washington University, USA.

Espada, R; Apan, A and McDougall, K (2017) Vulnerability assessment of urban community and critical infrastructures for integrated flood risk management and climate adaptation strategies. International Journal of Disaster Resilience in the Built Environment, 8(4), pp. 375-411. ISSN 1759-5916

Freitas, F and Mendes, J M (2019) Disaster, reconstruction, and data for social good: The case of wildfires in Portugal. International Journal of Disaster Resilience in the Built Environment, 10(4), pp. 239-247. ISSN 1759-5916

Funches Allen, Dawn (2025) Analyzing factors that contribute to cost overruns on department of defense (dod) contractor programs. DEngr thesis, George Washington University, USA.

Ganguly, I; Bowers, T; Eastin, I and Cantrell, R (2013) Role of green building programs in enhancing the usage of environmentally certified wood in the U.S. Residential construction industry. International Journal of Construction Education and Research, 9(3), pp. 183-202. ISSN 1557-8771

George, T. and Ganesan, V. (2026) Advanced cuttlefish optimizer-random decision forest (acordf) based design of fractional order pid controller for higher-order time-delay system. Journal of Engineering, Design and Technology, 24(4), pp. 1-34. ISSN 1726-0531

Gines, J A (2024) Mass timber utilization in architecture: Carbon sequestration, building materials and construction practices. PhD thesis, Mississippi State University, USA.

Goto, Y (2012) Sustainable wooden building concept for central Japan. DSc thesis, ETH Zürich, Switzerland.

Gui, X; Xiong, Y and Gou, Z (2024) A study of rainwater tank adoption in Australian households: Selecting the right size for better water-saving performance. Architectural Engineering and Design Management, 20(6), pp. 1648-1668. ISSN 1745-2007

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

Gutierres, Henrique Elias Pessoa (2019) Methodological proposal for the evaluation of geomorphological impacts based on the environmental impact studies of the Serro Azul and Igarapeba dams in the state of Pernambuco. PhD thesis, Universidade Federal de Pernambuco, Brazil.

Göswein, V; Arehart, J; Phan-Huy, C; Pomponi, F and Habert, G (2022) Barriers and opportunities of fast-growing biobased material use in buildings. Buildings & Cities, 3(1), pp. 745-755. ISSN 2632-6655

Han, Q and Keeffe, G (2020) Stepping stones: Assessing the permeability of urban greenspaces to climate-driven migration of trees. Smart and Sustainable Built Environment, 9(3), pp. 246-257. ISSN 2046-6099

Helaly, H; El-Rayes, K; Ignacio, E J and Joan, H J (2025) Comparison of machine-learning algorithms for estimating cost of conventional and accelerated bridge construction methods during early design phase. Journal of Construction Engineering and Management, 151(3): 04025004, ISSN 0733-9364

Hinze, J and Couey, J (1989) Weather in construction contracts. Journal of Construction Engineering and Management, 115(2), pp. 270-283. ISSN 0733-9364

Hussein, M K; Yusof, M J M and Jaafar, N S (2020) An observational study on forest landscape conservation in Malaysia via the establishment of forestry educational centres. Journal of Construction in Developing Countries, 25(2), pp. 153-173. ISSN 1823-6499

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

Jeong, E; Jang, J; Kim, T W and Lee, S (2025) Divide-and-conquer-based stratified models for predicting precast concrete installation times. Journal of Construction Engineering and Management, 151(9): 05025011, ISSN 0733-9364

Jiang, L; Zhao, T; Feng, C and Zhang, W (2023) Improvement of random forest by multiple imputation applied to tower crane accident prediction with missing data. Engineering, Construction and Architectural Management, 30(3), pp. 1222-1242. ISSN 0969-9988

Kalhor, E and Valentin, V (2018) Cost estimation framework for optimal retrofit planning to mitigate residential building vulnerability to wildfires. Journal of Construction Engineering and Management, 144(4): 05018003, ISSN 0733-9364

Kamath, M V; Prashanth, S; Kumar, M and Tantri, A (2024) Machine-learning-algorithm to predict the high-performance concrete compressive strength using multiple data. Journal of Engineering, Design and Technology, 22(2), pp. 532-560. ISSN 1726-0531

Karki, S and Hadikusumo, B (2023) Machine learning for the identification of competent project managers for construction projects in Nepal. Construction Innovation, 23(1), pp. 1-18. ISSN 1471-4175

Koc, K; Budayan, C; Ekmekcioǧlu, Ö and Tokdemir, O B (2024) Predicting cost impacts of nonconformances in construction projects using interpretable machine learning. Journal of Construction Engineering and Management, 150(1): 04023143, ISSN 0733-9364

Koc, K; Ekmekcioğlu, Ö and Gurgun, A P (2023) Prediction of construction accident outcomes based on an imbalanced dataset through integrated resampling techniques and machine learning methods. Engineering, Construction and Architectural Management, 30(9), pp. 4486-4517. ISSN 0969-9988

Koc, K; Ekmekcioǧlu, Ö and Gurgun, A P (2023) Developing a national data-driven construction safety management framework with interpretable fatal accident prediction. Journal of Construction Engineering and Management, 149(4): 04023010, ISSN 0733-9364

Koo, H. J.; Guerra, B. C.; Saka, S. and Leite, F. (2026) Streamlining BIM coordination and clash resolution through risk and relevance analysis. Journal of Construction Engineering and Management, 152(7): 04026092, ISSN 0733-9364

Kua, H W (2006) The design of effective policies for the promotion of sustainable construction materials. PhD thesis, Massachusetts Institute of Technology, USA.

Lee, Y Y R; Samad, H and Miang Goh, Y (2020) Perceived importance of authentic learning factors in designing construction safety simulation game-based assignment: Random forest approach. Journal of Construction Engineering and Management, 146(3): 04020002, ISSN 0733-9364

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

Liu, X; Song, Y; Yi, W; Wang, X and Zhu, J (2018) Comparing the random forest with the generalized additive model to evaluate the impacts of outdoor ambient environmental factors on scaffolding construction productivity. Journal of Construction Engineering and Management, 144(6): 04018037, ISSN 0733-9364

Ma, J (2016) A data driven study on LEED credits and green building related implications in city planning. PhD thesis, Hong Kong University of Science and Technology, Hong Kong.

Milošević, I; Kovačević, M and Petronijević, P (2021) Estimating residual value of heavy construction equipment using ensemble learning. Journal of Construction Engineering and Management, 147(7): 04021073, ISSN 0733-9364

Momade, M H; Shahid, S; Hainin, M R B; Nashwan, M S and Tahir Umar, A (2022) Modelling labour productivity using SVM and rf: A comparative study on classifiers performance. International Journal of Construction Management, 22(10), pp. 1924-1934. ISSN 1562-3599

Obasi, S N N; Pemberton, J and Awe, O O (2025) A comparative study of soil classification machine learning models for construction management. International Journal of Construction Management, 25(5), pp. 584-593. ISSN 1562-3599

Ochiai, C (2022) Windbreak stonewalls in a mountainous village of Japan: A case study of tsuchigoya in hongu-cho, tanabe city. International Journal of Disaster Resilience in the Built Environment, 13(2), pp. 197-210. ISSN 1759-5916

Ottaviani, F M; De Marco, M; Audisio, A; Wong, J and Belack, C (2024) A brief review of artificial intelligence techniques for conceptual cost estimation in construction projects. In: Thomson, C (ed.) Proceedings of 40th Annual ARCOM Conference, 2-4 September 2024, London South Bank University, UK.

Pandey, S; Paudel, S; Devkota, K; Kshetri, K and Asteris, P G (2025) Machine learning unveils the complex nonlinearity of concrete materials' uniaxial compressive strength. International Journal of Construction Management, 25(6), pp. 635-649. ISSN 1562-3599

Patel, T; Scheepbouwer, E and van der Walt, J D (2025) Optimizing infrastructure procurement: A predictive model for procurement delivery method selection in New Zealand context. International Journal of Construction Management, 25(14), pp. 1736-1748. ISSN 1562-3599

Praveen, D and Kunnampalli, J (2024) Evaluating the impacts of anticipated sea level rise, climate change and land use land cover scenarios on the rice crop in Alappuzha, Kerala and strategies to build climate responsive agriculture. International Journal of Disaster Resilience in the Built Environment, 15(4), pp. 755-775. ISSN 1759-5916

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

Ruokamo, E; Franzini, F; Lähtinen, K and Toppinen, A (2024) To renovate or build with wood? Results from Finnish citizen survey data. Construction Management and Economics, 42(10), pp. 886-901. ISSN 01446193

Sadeghi, S.; Niu, C.; Marjani, T. and Lotfi, R. (2026) Machine learning-enabled construction project management: Systematic review, comparative performance synthesis and implementation framework. Built Environment Project and Asset Management, 16(3), pp. 461-483. ISSN 2044-124X

Salarian, A A; Etemadfard, H; Rahimzadegan, A and Ghalehnovi, M (2023) Investigating the role of clustering in construction-accident severity prediction using a heterogeneous and imbalanced data set. Journal of Construction Engineering and Management, 149(2): 04022161, ISSN 0733-9364

Selvam, G.; Kamalanandhini, M.; Velpandian, M.; Hariharan, R.; Mohanakrishna, S. and Thirumurugan, V. (2026) Integrated statutory waste management framework for the sustainable built environment. Engineering, Construction and Architectural Management, 33(5), pp. 4078-4097. ISSN 0969-9988

Shan, B; Chen, B; Wen, J and Xiao, Y (2023) Thermal performance of cross-laminated timber (CLT) and cross-laminated bamboo and timber (clbt) panels. Architectural Engineering and Design Management, 19(5), pp. 511-530. ISSN 1745-2007

Sharma, V; Zaki, M; Jha, K N and Krishnan, N M A (2022) Machine learning-aided cost prediction and optimization in construction operations. Engineering, Construction and Architectural Management, 29(3), pp. 1241-1257. ISSN 0969-9988

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.

Smith, B A V (2016) Assessment of carbon and nutrient export from a peatland windfarm construction site. PhD thesis, University of Glasgow, UK.

Smith, D J (2003) Ecological effects of roads: Theory, analysis, management, and planning considerations. PhD thesis, University of Florida, USA.

Snyder, J R; Stephenson, L C; Mackie, J E and Smith, S D (2016) Agent-based modelling and the byzantine: Understanding the construction of antiquity's largest infrastructure project. In: Chan, P W and Neilson, C J (eds.) Proceedings of 32nd Annual ARCOM Conference, 5-7 September 2016, Manchester, UK.

Sohrabi, H and Noorzai, E (2024) Risk-supported case-based reasoning approach for cost overrun estimation of water-related projects using machine learning. Engineering, Construction and Architectural Management, 31(2), pp. 544-570. ISSN 0969-9988

Song, R; Gao, X; Nan, H; Zeng, S and Tam, V W Y (2024) Ecological restoration for mega-infrastructure projects: a study based on multi-source heterogeneous data. Engineering, Construction and Architectural Management, 31(9), pp. 3653-3678. ISSN 0969-9988

Stehn, L (2002) Environmental labelling of timber-framed dwellings and their building components. Building Research & Information, 30(4), pp. 248-254. ISSN 0961-3218

Sulaimon, I A; Alaka, H; Olu-Ajayi, R; Ahmad, M; Ajayi, S and Hye, A (2024) Effect of traffic data set on various machine-learning algorithms when forecasting air quality. Journal of Engineering, Design and Technology, 22(3), pp. 1030-1056. ISSN 1726-0531

Taheri, Ali (2024) The framework of an infrastructure performance model based on the concepts of civil integrated management (CIM). PhD thesis, Florida State University, USA.

Tan, P Y; Feng, Y and Hwang, Y H (2016) Deforestation in a tropical compact city (Part A): Understanding its socio-ecological impacts. Smart and Sustainable Built Environment, 5(1), pp. 47-72. ISSN 2046-6099

Teebken, J (2024) Disrupt and unlock? The role of actors in urban adaptation path-breaking. Buildings & Cities, 5(1), pp. 162-181. ISSN 2632-6655

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

Thomas, Douglas N (2015) The increase of timber use in residential construction in Australia: Towards a sustainable residential development model. PhD thesis, University of Technology Sydney, Australia.

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

Wang, Z; Hu, T; Liu, J; Xia, B; Bao, Z and Zhao, N (2025) The spatial correlation network and driving factors of economic resilience in the construction sector: Evidence from China. Construction Management and Economics, 43(11), pp. 961-982. ISSN 0144-6193

Woldetsadik, E T (2025) A predictive model for estimating formwork and shoring removal time. DEngr thesis, George Washington University, USA.

Wu, X.; Schmidt, R.; Wilcockson, T. D.; Wang, W. and Liu, H. (2026) Eye-tracking and place attachment: Visual and emotional engagement in higher education atrium spaces. Building Research & Information, 54(5), pp. 652-669. ISSN 0961-3218

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

Xia, X; Xiang, P; Khanmohammadi, S; Gao, T and Arashpour, M (2024) Predicting safety accident costs in construction projects using ensemble data-driven models. Journal of Construction Engineering and Management, 150(7): 04024054, ISSN 0733-9364

Zhou, X; Wang, Y and Gong, E (2025) Investigation of the factors driving engineering insurance consumption in china’s construction industry: A hybrid approach. Engineering, Construction and Architectural Management, 32(5), pp. 3236-3258. ISSN 0969-9988

van Niekerk, J; Wium, J and de Koker, N (2022) The value of data from construction project site meeting minutes in predicting project duration. Built Environment Project and Asset Management, 12(5), pp. 738-753. ISSN 2044-124X