Preliminary quantity estimate of highway bridges using neural networks

G. Morcous, M. M. Bakhoum, M. A. Taha, M. El-Said

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

An artificial neural networks (ANN) model with back-propagation learning algorithm were employed to transfer the knowledge encapsulated in the design of 22 overhead prestressed concrete (PC) bridges. The model was developed to estimate the concrete volume and prestressing weight in the superstructure of bridge navigable spans. The results indicated the great potential of ANN to be decision support tools for preliminary quantity estimates.

Original languageEnglish (US)
Title of host publicationProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering
EditorsB.H.V. Topping, B. Kumar
Pages51-52
Number of pages2
StatePublished - 2001
Externally publishedYes
EventProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering - Vienna, Austria
Duration: Sep 19 2001Sep 21 2001

Publication series

NameProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering

Conference

ConferenceProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering
Country/TerritoryAustria
CityVienna
Period9/19/019/21/01

Keywords

  • Bidding process
  • Conceptual design
  • Cost estimation
  • Highway bridges
  • Neural network
  • Quantity estimate

ASJC Scopus subject areas

  • Engineering(all)

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