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ART networks in automated conceptual design of structural systems

โœ Scribed by P. Hajela; B. Fu; L. Berke

Publisher
Elsevier Science
Year
1993
Weight
844 KB
Volume
4
Category
Article
ISSN
0956-0521

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โœฆ Synopsis

The present paper examines applications of adaptive resonance theory (ART) based neural networks in structural design. ART networks are vector classifiers, and their proposed use in the present work is to classify given conceptual design situations into one of several categories for which solutions are known. Once such a category is established, the actual generation of design is relegated to a procedural process associated with the category. In the present work, this approach is applied to the design of beam and frame structures for minimum weight and for maximum load carrying capacity. For such problems, the significant issues are shown to reside in selection of problem features used in the model abstraction, and in the choice of network parameters during training and classification.

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