Jaewook Jeong 
- (2024): Systematic Review of Quantitative Risk Quantification Methods in Construction Accidents. In: Buildings, v. 14, n. 10 (8 October 2024).
- (2024): Current Research and Future Directions for Off-Site Construction through LangChain with a Large Language Model. In: Buildings, v. 14, n. 8 (23 July 2024).
- (2024): Quantitative Accident Risk Estimation for Infrastructure Facilities Based on Accident Case Analysis. In: Buildings, v. 14, n. 5 (24 April 2024).
- (2024): Sustainability in Prefabricated Construction: Enhancing Multicriteria Analysis and Prediction Using Machine Learning. In: Journal of Construction Engineering and Management, v. 150, n. 8 (August 2024).
- (2024): Data-driven automatic classification model for construction accident cases using natural language processing with hyperparameter tuning. In: Automation in Construction, v. 164 (August 2024).
- (2023): Evaluation of Mobile Risk Perception Training System for Improving the Safety Awareness of Construction Workers. In: Buildings, v. 13, n. 12 (22 November 2023).
- (2023): Assessing Dust Emissions, Health Impacts, and Accident Risks in Prefabricated and Conventional Construction: A Comprehensive Comparative Study. In: Buildings, v. 13, n. 9 (23 August 2023).
- (2023): Quantitative methodology of environmental impact and economic assessment under equivalent conditions for prefabricated systems. In: Journal of Building Engineering, v. 76 (October 2023).
- (2023): Establishment of outdoor thermal comfort index groups for quantifying climate impact on construction accidents. In: Sustainable Cities and Society, v. 91 (April 2023).
- (2023): Quantitative Risk Evaluation by Building Type Based on Probability and Cost of Accidents. In: Buildings, v. 13, n. 2 (14 February 2023).
- (2022): Data-driven approach to develop prediction model for outdoor thermal comfort using optimized tree-type algorithms. In: Building and Environment, v. 226 (December 2022).
- (2022): Cost Overrun Risk Assessment and Prediction in Construction Projects: A Bayesian Network Classifier Approach. In: Buildings, v. 12, n. 10 (20 September 2022).
- (2022): Quantitative Analysis of the Accident Prevention Costs in Korean Construction Projects. In: Buildings, v. 12, n. 10 (20 September 2022).
- (2022): A Novel Safety Risk Assessment Based on Fuzzy Set Theory and Decision Methods in High-Rise Buildings. In: Buildings, v. 12, n. 12 (1 December 2022).
- (2022): Learning-driven construction productivity prediction for prefabricated external insulation wall system. In: Automation in Construction, v. 141 (September 2022).
- (2022): Empirical Analysis of Dust Health Impacts on Construction Workers Considering Work Types. In: Buildings, v. 12, n. 8 (31 July 2022).
- (2022): Quantitative Risk Evaluation of Fatal Incidents in Construction Based on Frequency and Probability Analysis. In: Journal of Management in Engineering (ASCE), v. 38, n. 2 (March 2022).
- (2021): Novel approach of the integrated work & risk breakdown structure for identifying the hierarchy of fatal incident in construction industry. In: Journal of Building Engineering, v. 41 (September 2021).
- (2021): Mix design optimization and environmental impact assessment of low-carbon materials containing alkali-activated slag and high CaO fly ash. In: Construction and Building Materials, v. 267 (January 2021).
- (2016): Establishing environmental benchmarks to determine the environmental performance of elementary school buildings using LCA. In: Energy and Buildings, v. 127 (September 2016).
- (2017): A simplified estimation model for determining the optimal rooftop photovoltaic system for gable roofs. In: Energy and Buildings, v. 151 (September 2017).
- (2016): Development of an evaluation process for green and non-green buildings focused on energy performance of G-SEED and LEED. In: Building and Environment, v. 105 (August 2016).
- (2016): Model for Evaluating the Financial Viability of the BOT Project for Highway Service Areas in South Korea. In: Journal of Management in Engineering (ASCE), v. 32, n. 2 (March 2016).
Structurae cooperates with
