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Al-Hussein, M, Alkass, S and Moselhi, O (2005) Optimization Algorithm for Selection and on Site Location of Mobile Cranes. Journal of Construction Engineering and Management, 131(05), 579–90.

Bernold, L E (2005) Paradigm Shift in Construction Education is Vital for the Future of Our Profession. Journal of Construction Engineering and Management, 131(05), 533–9.

Dunston, P S, Gambatese, J A and McManus, J F (2005) Assessing State Transportation Agency Constructability Implementation. Journal of Construction Engineering and Management, 131(05), 569–78.

El-Diraby, T E and Kashif, K F (2005) Distributed Ontology Architecture for Knowledge Management in Highway Construction. Journal of Construction Engineering and Management, 131(05), 591–603.

Georgy, M E, Chang, L and Zhang, L (2005) Prediction of Engineering Performance: A Neurofuzzy Approach. Journal of Construction Engineering and Management, 131(05), 548–57.

  • Type: Journal Article
  • Keywords: Performance evaluation; Predictions; Construction industry; Models; Neural networks; Fuzzy sets;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:5(548)
  • Abstract:
    Engineering and design professionals constitute a major driving force for a successful project undertaking. Although the industry has been active in addressing the performance of construction labor and methods to estimate or predict such performance, relatively fewer efforts have been conducted for the engineering profession. In an attempt to fill out this gap, the paper presents a study to utilize neurofuzzy intelligent systems for predicting the engineering performance in a construction project. First, neurofuzzy systems are introduced as integrated schemes of artificial neural networks and fuzzy control systems. The use of these neurofuzzy intelligent systems, particularly fuzzy neural networks, in predicting engineering performance is then demonstrated in the industrial construction sector. The development of the system is based on actual project data that was collected through questionnaire surveys. Statistical variable reduction techniques are further employed to develop linear regression models of the same engineering performance prediction scheme, and results are being compared between both techniques.

Georgy, M E, Chang, L and Zhang, L (2005) Utility-Function Model for Engineering Performance Assessment. Journal of Construction Engineering and Management, 131(05), 558–68.

Hegazy, T and Zhang, K (2005) Daily Windows Delay Analysis. Journal of Construction Engineering and Management, 131(05), 505–12.

Hegazy, T, Elbeltagi, E and Zhang, K (2005) Keeping Better Site Records Using Intelligent Bar Charts. Journal of Construction Engineering and Management, 131(05), 513–21.

Kim, K and de la Garza, J M (2005) Evaluation of the Resource-Constrained Critical Path Method Algorithms. Journal of Construction Engineering and Management, 131(05), 522–32.

Lueke, J S and Ariaratnam, S T (2005) Surface Heave Mechanisms in Horizontal Directional Drilling. Journal of Construction Engineering and Management, 131(05), 540–7.

Sacks, R, Navon, R, Brodetskaia, I and Shapira, A (2005) Feasibility of Automated Monitoring of Lifting Equipment in Support of Project Control. Journal of Construction Engineering and Management, 131(05), 604–14.