Study on the Filtering Method of Wind Monitoring Data in High Speed Railway Wind monitoring data filtering for high speed railway disaster monitoring system based on BPNN

Wind monitoring system is a subsystem of high-speed railway disaster monitoring system, how to obtain the accumulated wind monitoring data has an effect on the accuracy and reliability of wind alarm. In this paper, based on existing wind monitoring data, using neural network algorithm, we try to study the filtering method of wind monitoring data in high speed railway. According to the continuous learning of historical wind monitoring data, a better neural network model can be obtained. Furthermore, the wind monitoring data can be filtered by this model, and more accurate wind monitoring data can be obtained. Finally, the example can be used to verify the accuracy of the model. This study has a certain reference value for the quality control of wind speed monitoring data of high speed railway.