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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(05).

Asadian, E, Azeez, S, Leicht, R M and Asadi, S (2024) Exploring the barriers to women in construction and the opportunities presented through lean. Journal of Construction Engineering and Management, 150(05).

Henao, Y, Grubert, E, Korey, M, Bank, L C and Gentry, R (2024) Life cycle assessment and life cycle cost analysis of repurposing decommissioned wind turbine blades as high-voltage transmission poles. Journal of Construction Engineering and Management, 150(05).

Huang, Y, Liu, D, Bell, F M, Yu, J and Pena-Mora, F (2024) Influences of intra- and interorganizational IT innovations on knowledge sharing and team creativity: Evidence from construction projects in China. Journal of Construction Engineering and Management, 150(05).

Min, Y and Lee, H W (2024) Adoption inequalities and causal relationship between residential electric vehicle chargers and heat pumps. Journal of Construction Engineering and Management, 150(05).

Nabi, M A, El-Adaway, I H and Assaad, R H (2024) Modeling inflation transmission among different construction materials. Journal of Construction Engineering and Management, 150(05).

Nguyen, P H D and Tran, D (2024) Exploring the use of quality control plans for alternative contracting methods in highway projects. Journal of Construction Engineering and Management, 150(05).

Ning, X, Ye, X, Li, H, Rajendra, D and Skitmore, M (2024) Evolutionary game analysis of optimal strategies for construction stakeholders in promoting the adoption of green building technology innovation. Journal of Construction Engineering and Management, 150(05).

Shi, M, Chen, C, Xiao, B and Seo, J (2024) Vision-based detection method for construction site monitoring by integrating data augmentation and semisupervised learning. Journal of Construction Engineering and Management, 150(05).

Tao, Y, Hu, H, Xu, F and Zhang, Z (2024) Work-rest schedule optimization of precast production considering workers' overexertion. Journal of Construction Engineering and Management, 150(05).

Turkoglu, H, Arditi, D and Polat, G (2024) Augmented time-cost trade-off optimization using particle swarm optimization. Journal of Construction Engineering and Management, 150(05).

Wang, H, Xu, S, Cui, D, Xu, H and Luo, H (2024) Information integration of regulation texts and tables for automated construction safety knowledge mapping. Journal of Construction Engineering and Management, 150(05).

Wang, J, Liang, M and Liao, P C (2024) Toward an intuitive device for construction hazard recognition management: Eye fixation-related potentials in reinvestigation of hazard recognition performance prediction. Journal of Construction Engineering and Management, 150(05).

Wang, L, Lee, J, Nimawat, J, Han, K and Gupta, A (2024) Integrated 4D design change management model for construction projects. Journal of Construction Engineering and Management, 150(05).

Wang, S, Hasan, M and Lu, M (2024) Global sensitivity analysis methodology for construction simulation models: Multiple linear regressions versus multilayer perceptions. Journal of Construction Engineering and Management, 150(05).

  • Type: Journal Article
  • Keywords: explainable artificial intelligence; multilayer perception; multiple linear regression; productivity model; sensitivity analysis
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-14059
  • Abstract:
    In this research, the multilayer perceptron (MLP), also known as error backpropagation neural networks, is made transparent and explainable by contrasting with the commonly applied multiple linear regression (MLR). A novel MLP-based method for performing global sensitivity analysis is formalized to tackle complicated, nonexplainable simulation models or artificial intelligence (AI) models, which were developed to support critical decisions in construction engineering. The sensitivity analysis results serve as further evidence to validate the decision support models and lend new insights into the problems under investigation. The proposed new method was applied in two case studies in construction engineering, they are: precast viaduct installation cycles and concrete strength development. In both applications, the results of sensitivity analysis were represented in straightforward forms and effectively cross-checked with the existing knowledge of the problem domain or the experiences of construction practitioners.

Zhang, S, Hua, X and Shi, X (2024) Measurement for risk perception ability. Journal of Construction Engineering and Management, 150(05).