Study of Suspension Bridge Deformation Using Neural Network

Abstract

Abstract-Suspension bridges are an important and widely used element of regional and urban infrastructure for traffic and transportation. One of the elements of the system to ensure their safety and security is the geodetic monitoring by using GNSS technologies. Displacement of the bridges points depend not only on time, the impact of traffic capacity and wind on the naturaltechnical system of suspension bridge should be taken into consideration. This makes the task of constructing a predictive model difficult. The most significant effects are the temperature change, the impact of wind and vehicle movement. Here is some analysis of these effects on the dynamics of a suspension bridge using real experimental data. Two analytical methods, namely Neural Networks (NN) and Least Square (LS), were used for the prediction of the effects on the behavior of suspension bridges. The results of the Neural Networks give better picture than the results of Least Square.