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Wang, J.X., Liu C.H., Shan, X.H. and Zhu, J.S. (2010) Railway Passenger Volume Forecast Based on Two-Level Orthogonal Neural Network Model. China Railway Science, 32, 126-132.

has been cited by the following article:

• TITLE: Research on Railway Passenger Flow Prediction Method Based on GA Improved BP Neural Network

  AUTHORS: Jian Zhang, Weihao Guo

  KEYWORDS: Railway Passenger Flow, Prediction, BP Neural Network, Genetic Algorithm

  JOURNAL NAME: Journal of Computer and Communications, Vol.7 No.7, July 31, 2019

  ABSTRACT: This paper chooses passenger flow data of some stations in China from January 2015 to March 2016, and the time series prediction model of BP neural network for railway passenger flow is established. But because of its slow convergence speed and easily falling into local optimal solution of the problem, we propose to improve the time series model of BP neural network by genetic algorithm to predict railway passenger flow. Experimental results show that the improved method has higher prediction accuracy and better nonlinear fitting ability.