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Study of Optimized Steel Truss Design Using Neural Network to Resist Lateral Loads

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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.

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Periodical:

Key Engineering Materials (Volumes 348-349)

Pages:

405-408

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.348-349.405

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Online since:

September 2007

Authors:

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

Keywords:

Genetic Algorithm (GA), Neural Network (NN), Steel Truss Structure, Structure Optimization Design

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© 2007 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] H. Adeli. Adavances in design optimization. Chapman & Hall. (1994).

Google Scholar

[2] István Kövesdi, etc. Application of Neural Networks in Structure Activity Relationships, 1999 John Wiley & Sons, Inc. PP: 249-269.

Google Scholar

[3] Simon Haykin. Neural networks; A comprehensive Foundation. Pretice-Hall (1999).

Google Scholar

[4] Wang, Jun et al. Computational Intelligence in Manufacturing Handbook, CRC Press LLC, (2001).

Google Scholar

[5] Zhang yougsheng. Multi-objective optimization design of anti-seismic structure considering ductility and cost. Journal of taiyuan university of technology. Vol 29. No. 3. May, 1998. PP: 291293.

Google Scholar

[6] W. Li, Y. Han. Multiobjective optimum design of structures. Computer aided optimum design of structure IV: Structural optimization. PP: 35-42.

Google Scholar