Prediction of Railway Passenger Traffic Volume based on Grey BP Neural Network

Research Area: Volume 8,Issue 2,Mar.,2019 Year: 2019
Type of Publication: Article Keywords: Railway Passenger Flow, Passenger Volume Prediction, Grey BP Neural Network Model, Nonlinear Series, Combination Model
Authors:
  • Yiming Sun
Journal: IJEIR Volume: 8
Number: 2 Pages: 97-104
Month: March
ISSN: 2277-5668
Abstract:
Railway passenger volume is an important basis for railway operation organization. Predicting railway passenger volume plays a key role in overall construction planning of railway. In order to make a better plan for future railway construction in China, improve the utilization ratio of railway and development of national economy, this paper combines the gray prediction model with the BP neural network model to predict railway passenger volume. Make preliminary prediction based on the railway passenger volume from 2008 to 2016 by using the gray prediction model, consider the continuity of passenger transportation demand, the data of next two years are combined and input into BP neural network for prediction, then obtain the railway passenger volume of the corresponding year, and the average relative error of the predicted results is 0.74%. The example proves that the prediction accuracy and speed of the grey BP neural network combination model are higher than that of the single gray prediction model, it is an effective nonlinear railway passenger volume prediction method and can assist the railway overall planning.

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