NEURAL NETWORK MODEL FOR PARAMETRIC COST ESTIMATION OF HIGHWAY PROJECTS

This paper used a neural network (NN) approach to effectively manage construction cost data and develop a parametric cost-estimating model for highway projects. Eighteen actual cases of highway projects constructed in Newfoundland, Canada, have been used as the source of cost data. Rather than using black-box NN software, a simple NN simulation has been developed in a spreadsheet format that is customary to many construction practitioners. As an alternative to NN training, two techniques were used to determine network weights: simplex optimization and genetic algorithms. Accordingly, the weights that produced the best cost prediction for the historical cases were used to find the optimum NN. To facilitate the use of this NN on new projects, a user-friendly interface was developed using spreadsheet macros to simplify user input and automate cost prediction. For practicality, sensitivity analysis and adaptation modules have also been incorporated to account for project uncertainty and to reoptimize the model on new historical data. Details regarding model development and capabilities have been discussed in an attempt to encourage practitioners to benefit from the NN technique.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/8675438
• Corporate Authors:

  American Society of Civil Engineers

  345 East 47th Street
  New York, NY  United States  10017-2398
• Authors:
  • Hegazy, T
  • Ayed, A
• Publication Date: 1998-5

Language

• English

Media Info

• Features: Appendices; Figures; References;
• Pagination: p. 210-218
• Serial:
  • Journal of Construction Engineering and Management
  • Volume: 124
  • Issue Number: 3
  • Publisher: American Society of Civil Engineers
  • ISSN: 0733-9364
  • EISSN: 1943-7862
  • Serial URL: http://ascelibrary.org/journal/jcemd4

Subject/Index Terms

• TRT Terms: Case studies; Construction; Construction projects; Cost estimating; Costs; Estimates; Genetic algorithms; Mathematical models; Mathematical prediction; Neural networks; Optimization; Parametric analysis; Psychological adaptation; Road construction; Sensitivity analysis; Simplex method; Spreadsheets
• Uncontrolled Terms: Construction costs
• Geographic Terms: Newfoundland and Labrador
• Subject Areas: Administration and Management; Construction; Data and Information Technology; Economics; Finance; Highways; Society; I10: Economics and Administration; I52: Construction of Pavements and Surfacings;

Filing Info

• Accession Number: 00750599
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 29 1998 12:00AM