American Society of Civil Engineers

Neural Networks in Civil Engineering. I: Principles and Understanding

by Ian Flood, A.M.ASCE, (Asst. Prof., Dept. of Civ. Engrg., Univ. of Maryland, College Park, MD 20742) and Nabil Kartam, A.M.ASCE, (Asst. Prof., Dept. of Civ. Engrg., Univ. of Maryland, College Park, MD)

Journal of Computing in Civil Engineering, Vol. 8, No. 2, April 1994, pp. 131-148, (doi:

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Document type: Journal Paper
Abstract: This is the first of two papers providing a discourse on the understanding, usage, and potential for application of artificial neural networks within civil engineering. The present paper develops an understanding of how these devices operate and explains the main issues concerning their use. A simple structural-analysis problem is solved using the most popular form of neural-networking system—a feedforward network trained using a supervised scheme. A graphical interpretation of the way in which neural networks operate is first presented. This is followed by discussions of the primary concepts and issues concerning their use, including factors affecting their ability to learn and generalize, the selection of an appropriate set of training patterns, theoretical limitations of alternative network configurations, and network validation. The second paper demonstrates the ways in which different types of civil engineering problems can be tackled using neural networks. The objective of the two papers is to ensure the successful development and application of this technology to civil engineering problems.

ASCE Subject Headings:
Neural networks
Civil engineering
Artificial intelligence
Computer applications