Application of Artificial Neural Network for Recovering GPS—RTK Data in the Monitoring of Cable-Stayed Bridge Deformation

GPS in the cable-stayed bridge monitoring system is used to provide overall deformation measurements of the bridge. During GPS data acquisition, data may be lost under the impact of various factors. This paper investigates the application of the artificial neuron network (ANN) method to recover lost GPS data under the influence of factors such as wind speed, air temperature, and stress of structure. Monitoring data of an actual cable-stayed bridge were extracted for study. The proposed method results are compared with actual monitoring data to evaluate the accuracy. These results indicate that GPS—RTK data supplemented by the ANN method completely ensure accuracy and reliability.