Identification of structural systems by neural networks

Anastassios G. Chassiakos and Sami F. Masri

Mathematics and Computers in Simulation (MATCOM), 1996, vol. 40, issue 5, 637-656

Abstract: A method based on the use of neural networks is developed for the identification of systems encountered in the field of structural dynamics. The methodology is applied to the identification of linear and nonlinear dynamic systems such as the damped Duffing oscillator and the Van der Pol equation. The “generalization” ability of the neural networks is used to predict the response of the identified systems under deterministic and stochastic excitations. It is shown that neural networks provide high fidelity models of unknown structural dynamic systems, which are used in applications such as structural control, health monitoring of structures, earthquake engineering, etc.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:40:y:1996:i:5:p:637-656

DOI: 10.1016/0378-4754(95)00012-7

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