Abstract：Based on the existing experimental results of long-span bridges in the wind tunnel laboratory of Tongji University, a database system for wind-resistant performance of long-span bridges is integrated by Access Database software and Java programming language. Based on the artificial neural network technology, artificial neurons were trained and neuron connection weights were adjusted, and consequently the intelligent identification method of aerodynamic parameters (including aerostatic coefficients and aerodynamic derivatives) was established. This method is mainly aiming at flat box girder section and inverted trapezoidal box girder section. The errors between the neural network output and the expected output can meet the expected requirement, and the prediction results can be referred in the preliminary wind-resistant design of bridge structures.
