Study of optimized steel truss design using neural network to resist lateral loads

Young S. Cho, Lin Xia, Seong U. Hong, Seong B. Kim, Jun S. Bae

Research output: Contribution to journalArticle

Abstract


Structural optimization is widely adopted in the design of structures with the development of computer aided design (CAD) and the development of computer technique recently. By applying the artificial neural network to structural optimization, designers can gain the design scheme of structures more feasibly and easily. In this paper, the genetic algorithm (GA) used in the error back-propagation (BP) network is applied to get the optimization result of the structural system. And the training pair of BP neural network is obtained from the structural analysis using a finite element program. The case study of 10 member truss structure using GA and BP will be helpful to reduce the cost of structures which is related to weight and the dynamic performance of optimization under the lateral load.
Original languageEnglish
Pages (from-to)405-408
Number of pages4
JournalKey Engineering Materials
Volume348-349
DOIs
Publication statusPublished - 2007
Externally publishedYes

Fingerprint

Steel
Backpropagation
Structural optimization
Neural networks
Genetic algorithms
Structural analysis
Computer aided design
Costs

Keywords

  • Structure optimization design
  • Neural network
  • Steel truss structure
  • Genetic algorithm

Cite this

Cho, Young S. ; Xia, Lin ; Hong, Seong U. ; Kim, Seong B. ; Bae, Jun S. / Study of optimized steel truss design using neural network to resist lateral loads. In: Key Engineering Materials. 2007 ; Vol. 348-349. pp. 405-408.
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Study of optimized steel truss design using neural network to resist lateral loads. / Cho, Young S.; Xia, Lin; Hong, Seong U.; Kim, Seong B.; Bae, Jun S.

In: Key Engineering Materials, Vol. 348-349, 2007, p. 405-408.

Research output: Contribution to journalArticle

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