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LISS 2012 pp 543-552 | Cite as

A Comparative Study on Predict Effects of Railway Passenger Travel Choice Based on Two Soft Computing Methods

  • Yan Xi
  • Li Zhu-Yi
  • Long Cheng-Xu
  • Kang Shu
  • Gao Yue
  • Li Jing
Conference paper

Abstract

The travelling factors acting on the railway passengers changes greatly with the passengers’ choice. With the help of the modern information computing technology, the factors were integrated to realize quantitative analyze according to the travel purpose and travel cost. The detailed comparative study was implemented with the two soft computing method: genetic algorithm, BP neural network. The two methods with different idea, applicable range applicable and the key parameters set were also studied in this model. The analyzed methods were also proved effective and applied for predicting the railway passengers travel choice through the empirical study with soft-computing supporting.

Keywords

Railway Passenger Travel Choice Genetic Algorithm BP Neural Network Comparative 

Notes

Acknowledgment

This paper is supported by the National Natural Science Foundation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yan Xi
    • 1
  • Li Zhu-Yi
    • 2
  • Long Cheng-Xu
    • 1
  • Kang Shu
    • 1
  • Gao Yue
    • 1
  • Li Jing
    • 1
  1. 1.School of Economic and ManagementBeijing Jiaotong UniversityBeijingChina
  2. 2.Computer Science Engineering ChampaignUniversity of Illinois, Urbana ChampaignUrbanaUSA

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