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Bashford, H H, Walsh, K D and Sawhney, A (2005) Production System Loading–Cycle Time Relationship in Residential Construction. Journal of Construction Engineering and Management, 131(01), 15–22.

Chen, Z, Li, H and Wong, C T C (2005) {[}EnvironalPlanning{]}: Analytic Network Process Model for Environmentally Conscious Construction Planning. Journal of Construction Engineering and Management, 131(01), 92–101.

Chester, M and Hendrickson, C (2005) Cost Impacts, Scheduling Impacts, and the Claims Process during Construction. Journal of Construction Engineering and Management, 131(01), 102–7.

Dzeng, R J, Tserng, H P and Wang, W C (2005) Automating Schedule Review for Expressway Construction. Journal of Construction Engineering and Management, 131(01), 127–36.

Elazouni, A M, Ali, A E and Abdel-Razek, R H (2005) Estimating the Acceptability of New Formwork Systems Using Neural Networks. Journal of Construction Engineering and Management, 131(01), 33–41.

  • Type: Journal Article
  • Keywords: Neural networks; Decision making; Artificial intelligence; Data collection; Construction management; Egypt;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:1(33)
  • Abstract:
    Continual development in construction techniques results in emergence of specialized formwork systems. A new system will have to compete with in-use systems for adoption in a target operation. Thus, it is essential that decision makers anticipate the acceptability of new systems before making decisions to acquire them. Estimating acceptability basically assesses how features of a new system are comparable to that of in-use systems. Therefore, analogy is a focal factor for the acceptability estimating process. Neural networks (NNs) are more suitable to model construction problems requiring analogy-based solutions. A NN-based approach was employed to anticipate the acceptability of new formwork systems. The study collected data from a group of 40 users in Egypt. A set of six performance characteristics that mostly pertain to acceptability estimating were identified. The study used the analytical hierarchy process to produce pairs of a performance characteristics’ vector and the corresponding acceptability value, and utilized the developed pairs to train NNs. Finally, tests on trained NNs using unseen data indicated satisfactory performance.

Horman, M J and Kenley, R (2005) Quantifying Levels of Wasted Time in Construction with Meta-Analysis. Journal of Construction Engineering and Management, 131(01), 52–61.

Kaiser, M J, Pulsipher, A G and Byrd, R C (2005) Cost of Abrasive Cutting in Decommissioning Operations in the Gulf of Mexico. Journal of Construction Engineering and Management, 131(01), 137–48.

Kaiser, M J, Pulsipher, A G and Martin, J (2005) Cost of Site Clearance and Verification Operations in the Gulf of Mexico. Journal of Construction Engineering and Management, 131(01), 117–26.

Oliveros, A V O and Fayek, A R (2005) Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating. Journal of Construction Engineering and Management, 131(01), 42–51.

Singh, D and Tiong, R L K (2005) A Fuzzy Decision Framework for Contractor Selection. Journal of Construction Engineering and Management, 131(01), 62–70.

Tatum, C B (2005) Building Better: Technical Support for Construction. Journal of Construction Engineering and Management, 131(01), 23–32.

Yiu, C Y, Ho, H K, Lo, S M and Hu, B Q (2005) Performance Evaluation for Cost Estimators by Reliability Interval Method. Journal of Construction Engineering and Management, 131(01), 108–16.

Zhang, X (2005) Critical Success Factors for Public–Private Partnerships in Infrastructure Development. Journal of Construction Engineering and Management, 131(01), 3–14.

Zhang, X (2005) Paving the Way for Public–Private Partnerships in Infrastructure Development. Journal of Construction Engineering and Management, 131(01), 71–80.

Zheng, D X M, Ng, S T and Kumaraswamy, M M (2005) Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization. Journal of Construction Engineering and Management, 131(01), 81–91.