Design of double layer grids using backpropagation neural networks

In this paper efficient neural networks are trained for design of double layer grids. Square diagonal-on-diagonal grids with spans varying between 26.5 and 75 m are considered. Backpropagation algorithm is employed for training efficient neural networks for evaluation of the maximum deflection, weight, and design of double layer grids. A special method is developed for data ordering to reduce the nonlinearity of the data and to increase the speed of training. This approach also provides the necessary stability. Additional neural nets are trained and tested for design of grids using the developed data ordering.