Forecasting method for urban rail transit ridership at station level using back propagation neural network

HIGHLIGHTS

• who: from the College of Transportation Engineering, Tongji University, Shanghai, China have published the article: Forecasting Method for Urban Rail Transit Ridership at Station Level Using Back Propagation Neural Network, in the Journal: (JOURNAL) of 11/05/2016
• what: In this paper a new variable population per distance band is considered and a back propagation neural network (BPNN) model which can reflect nonlinear relationship between ridership and its predictors is proposed to forecast ridership. This paper uses data of Tokyo, Japan, to illustrate how values of the above factors are calculated or obtained and the . . .
  

   

  

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