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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).

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002414
  • Abstract:
    Construction companies struggle with their hiring plans and react to economic shifts afterward, resulting in unnecessary layoffs and overhirings. A model that forecasts future construction hiring can help adjust hiring levels based on upcoming projections. This research proposes a framework for predicting the future sequence (upcoming 12 months) of hiring values instead of specific months, based on historical data between 1993 and 2022 for hiring and economic explanatory variables. Explanatory variables are categorized into the local, neighboring states, and national levels. Feature selection methods were used to filter out the initial data set to reduce data dimensionality—the output of each method trained by the recurrent neural network (RNN). Seq2seq models were evaluated based on their mean absolute error (MAE). The results of the best-performing model indicate that the multivariate seq2seq model can capture general trends and disruptions due to economic recession and natural disasters more accurately than the univariate statistical models, even though there was no feature inside the data set regarding hurricanes.

Damdelen, O and Tansu, A (2022) Influence of Recycled Plastic on the Thermal Transmittance and Sustainable Assessment of Concrete Mixes. Journal of Construction Engineering and Management, 148(12).

Kazar, G, Doğan, N B, Ayhan, B U and Tokdemir, O B (2022) Quality Failures–Based Critical Cost Impact Factors: Logistic Regression Analysis. Journal of Construction Engineering and Management, 148(12).

Khurana, M, Garvin, M J and Mahalingam, A (2022) Synthesis of Relational Practices for PPP Contracts and Their Linkage with Governance Mechanisms. Journal of Construction Engineering and Management, 148(12).

Li, S and Xu, Z (2022) System Configuration Design of BIM Object-Oriented Database for Civil Engineering. Journal of Construction Engineering and Management, 148(12).

Lin, S and Cheung, S O (2022) Exploring the Concept of Psychological Distance and Its Impact on Intention to Settle in Construction Dispute Negotiation. Journal of Construction Engineering and Management, 148(12).

Naumets, S, Lu, M and Ali, M (2022) Project Schedule Development under Environment-Induced Time-Window Constraints: Case of Constructing River-Crossing Bridge in Remote Northern Region. Journal of Construction Engineering and Management, 148(12).

Pirzadeh, P, Lingard, H and Zhang, R P (2022) Job Quality and Construction Workers’ Mental Health: Life Course Perspective. Journal of Construction Engineering and Management, 148(12).

Salazar, L A, Ballard, G, Arroyo, P and Alarcón, L F (2022) Development of a Commitment Management System for Construction Projects. Journal of Construction Engineering and Management, 148(12).

Shafique, F and Mollaoglu, S (2022) Shared Transformational Leadership for Green Architecture Engineering and Construction Project Teams: A Study of LEED Projects. Journal of Construction Engineering and Management, 148(12).

Shen, Y, Lin, Z and Wang, Z (2022) Single-Side Accumulative Jacking Construction Method for Large-Span Arched Latticed Shells. Journal of Construction Engineering and Management, 148(12).

Tommelein, I D (2022) Work Density Method for Takt Planning of Construction Processes with Nonrepetitive Work. Journal of Construction Engineering and Management, 148(12).

Wang, J, Han, J, Chen, J, Ding, G, Feng, G, Liu, T and Guo, B (2022) Experimental and Numerical Study on the Dynamic Response of a Superthick Backfill Subgrade under High-Speed Railway Loading: A Case Study of Qianjiang–Zhangjiajie–Changde Railway. Journal of Construction Engineering and Management, 148(12).

Zou, Y, Wu, Y, Guo, B H W, Papadonikolaki, E, Dimyadi, J and Hung, S N (2022) Investigating the New Zealand Off-Site Manufacturing Industry’s Readiness for Automated Compliance Checking. Journal of Construction Engineering and Management, 148(12).