Research on Forecast Model and Algorithm of Train Passenger Sending Volume

The forecast of the passenger volume of the railway station is to analyze the development trend of passenger traffic in the future. Correctly predicting the passenger volume will help to develop the local regional economy, rationally allocate resources and reduce operating costs. Although the gray prediction model is widely used in many fields, the smoothness of the original data sequence has a very important influence on the accuracy of the gray prediction model. In addition, many raw data sequences have low smoothness in practical applications, so the gray The field of use of predictive models is limited. A gray GM(1,1) model based on polynomial function transformation is proposed, and the model is applied to the prediction of train passenger volume in 2010-2013. The prediction results show that the prediction accuracy of the model is significantly higher than that. The prediction results of the GM(1,1) model have certain application value.