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 and Li Jing
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Yan Xi: Beijing Jiaotong University
Li Zhu-Yi: University of Illinois, Urbana Champaign
Long Cheng-Xu: Beijing Jiaotong University
Kang Shu: Beijing Jiaotong University
Gao Yue: Beijing Jiaotong University
Li Jing: Beijing Jiaotong University

A chapter in LISS 2012, 2013, pp 543-552 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-32054-5_77

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DOI: 10.1007/978-3-642-32054-5_77

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