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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 64
Edited by: B.H.V. Topping
Paper I.6

Neural Networks and Cold-formed Steel Design

E.M.A. El-Kassas, R.I. Mackie and A.I. El-Sheikh

Department of Civil Engineering, University of Dundee, Dundee, U.K.

Full Bibliographic Reference for this paper
E.M.A. El-Kassas, R.I. Mackie, A.I. El-Sheikh, "Neural Networks and Cold-formed Steel Design", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 37-43, 2000. doi:10.4203/ccp.64.1.6
The application of neural networks to cold-formed steel design is considered. Cold-formed steel design is more complex than hot-rolled steel design because of the large number of different section profiles, and traditional computing tools are not well-suited for dealing with this. The flexibility of neural networks makes them a suitable alternative. The paper describes the use of neural networks to predict the failure load of cold-formed sections, and the results are in good agreement with results from design codes.

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