Structural Engineering and Mechanics

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Application of artificial neural networks to the response prediction of geometrically nonlinear truss structures

  • Cheng, Jin (Dept.of Bridge Engineering, Tongji University) ;
  • Cai, C.S. (Dept. of Civil and Environmental Engineering, 3418H CEBA, Louisiana State University) ;
  • Xiao, Ru-Cheng (Dept. of Bridge Engineering, Tongji University)
  • Received : 2005.10.31
  • Accepted : 2007.01.08
  • Published : 2007.06.20
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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.

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