Techno Press
Techno Press

Structural Engineering and Mechanics
  Volume 26, Number 3, June20 2007 , pages 251-262
DOI: https://doi.org/10.12989/sem.2007.26.3.251
 


Application of artificial neural networks to the response prediction of geometrically nonlinear truss structures
Jin Cheng, C. S. Cai and Ru-Cheng Xiao

 
Abstract
    This paper examines the application of artificial neural networks (ANN) to the response prediction of geometrically nonlinear truss structures. Two types of analysis (deterministic and probabilistic analyses) are considered. A three-layer feed-forward backpropagation network with three input nodes, five hidden layer nodes and two output nodes is firstly developed for the deterministic response analysis. Then a back propagation training algorithm with Bayesian regularization is used to train the network. The trained network is then successfully combined with a direct Monte Carlo Simulation (MCS) to perform a probabilistic response analysis of geometrically nonlinear truss structures. Finally, the proposed ANN is applied to predict the response of a geometrically nonlinear truss structure. It is found that the proposed ANN is very efficient and reasonable in predicting the response of geometrically nonlinear truss structures.
 
Key Words
    artificial neural networks; geometrically nonlinear analysis; truss structures; uncertainties; response.
 
Address
Jin Cheng; Dept. of Bridge Engineering, Tongji University, Shanghai, 200092, China
C. S. Cai; Dept. of Civil and Environmental Engineering, 3418H CEBA, Louisiana State University,
Baton Rouge, LA 70803, USA
Ru-Cheng Xiao; Dept. of Bridge Engineering, Tongji University, Shanghai, 200092, China
 

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