@inproceedings{03c7f7b2b4f84106ac80bc8d176b6488,
title = "Preliminary quantity estimate of highway bridges using neural networks",
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.",
keywords = "Bidding process, Conceptual design, Cost estimation, Highway bridges, Neural network, Quantity estimate",
author = "G. Morcous and Bakhoum, {M. M.} and Taha, {M. A.} and M. El-Said",
year = "2001",
language = "English (US)",
isbn = "0948749792",
series = "Proceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering",
pages = "51--52",
editor = "B.H.V. Topping and B. Kumar",
booktitle = "Proceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering",
note = "Proceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering ; Conference date: 19-09-2001 Through 21-09-2001",
}