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

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.