Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 1 results ...

Alex, D P, Al Hussein, M, Bouferguene, A and Fernando, S (2010) Artificial Neural Network Model for Cost Estimation: City of Edmonton’s Water and Sewer Installation Services. Journal of Construction Engineering and Management, 136(07), 745–56.

  • Type: Journal Article
  • Keywords: Water distribution systems; Sewers; Installation; Costs estimation; Neural networks; California; Water and sewer installation services; Cost estimation; Artificial neural networks;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000184
  • Abstract:
    Over the years of the study (1999–2004) presented in this paper, the City of Edmonton, Canada’s Drainage and Maintenance Department has experienced an annual increase of about 12% in the installation of water and sewer services for residential facilities. According to the current estimating procedure, a discrepancy of up to 60% exists between the estimated and actual costs of these projects. A detailed analysis of all activities involved in the installation of the water and sewer services has been carried out and is presented in this paper. The proposed methodology, which is based upon the analysis of past data obtained from the City of Edmonton’s drainage division for the period of 1999–2004, is also presented. The methodology has been incorporated into a computer module, which integrates the concept of artificial neural network (ANN) with the current estimating system used by the City of Edmonton. The following research includes a description of the algorithm used in ANN, as well as an assessment of past data obtained from the city record for over 800 jobs (cases) performed over the period of the study.