Reduction of the Influential Factors of Railway Passenger Demand Based on Rough Set



In the background of the development of global low-carbon economy, to blossom the low-carbon transport is necessary for every country. Railway is recognized as a green transport with low-power consumption, less pollution, which is one of the most important infrastructures developed actively around the world. With the approaching era of high-speed railway, railway passenger demand has been paid much more attention. As passengers with different trip purposes are influenced by different factors when choosing means of transport, this paper will classify passengers by trip purposes and find the main influential factors according to different types of passengers with the aid of rough set. Then put forward initiatives aimed at improving passenger satisfaction, and enhance the positive attitude of passengers towards rail transportation.




Qi Luo






N. Ma et al., "Reduction of the Influential Factors of Railway Passenger Demand Based on Rough Set", Applied Mechanics and Materials, Vols. 58-60, pp. 112-117, 2011


June 2011




[1] Sauter-Servaes T, Nash A, Increasing Rail Demand by Improving Multimodal Information and Ticketing Results of the Night&Flight Case Study, TRANSPORTATION RESEARCH RECORD, 2009, pp: 7-13.

DOI: 10.3141/2117-02

[2] Ma Ning, Ding Jiaqi, Xie Feifei, Li Xuemei. Research on Influential Factors of the Satisfaction of Railway Passengers Based on Rough Set. 2010 International Conference on Computational Intelligence and Vehicular System Proceedings. 2010. 11. pp: 22-26.

[3] Hans Kremers, Peter Nijkamp, Piet Rietveld, A meta-analysis of price elastic ties of transport demand in a general equilibrium framework. Tinbergen Institute Discussion Paper, (2000).

DOI: 10.1016/s0264-9993(01)00073-6

[4] LI Yongwen. The Survey and Analysis of the Passenger's Satisfaction [J]. Railway Economics Research. 2002 (9): 33-35.

[5] ZHANG Xiuyuan. The Survey of Choice Intention in the Demand of Railway Fast Passenger Transport [J]. Technology Economics. 2004 (2): 59-60.

[6] FAN Lili. The Demand Function of Our Country's Overall Passenger Transport and the Demand Pattern for Various Passenger Transport Manner [J]. Journal of Industrial Engineering and Engineering Management. 2005 (4): 69-73.

[7] Lythgoe, W.F., Wardman, M., Toner, J.P. Enhancing Rail Passenger Demand Models to examine Station Choice and Access to the Rail Network. AET European Transport Conference. Strasbourg. (2004).

[8] XIAO Long-wen, SHI Feng. Optimization of Train of Mass Transit Type Plan [J]. Journal of Hunan University (Natural Sciences). 2009(1): 85-88.

[9] ZHOU Yuan-feng, JIA Yuan-hua, FANG Sheng-xiu. Research on Fuzzy Comprehensive Evaluation Method for Rail Passenger Satisfaction [J]. JOURNAL OF NORTHERN JIAOTONG UNIVERSITY. 2003 (10): 67-68.

[10] ZHANG Qi, YANG Hao. Comprehensive Evaluation of the Degree of Railway Passenger Satisfaction Based on Fuzzy Factors [J]. JOURNAL OF THE CHINA RAILWAY SOCIETY. 2006 (2): 23.

[11] HE Yu-qiang, MAO Bao-hua , CHEN Tuan-sheng, YANG Jing. The Mode Share Model of the High-speed Passenger Railway Line and Its Application [J]. JOURNAL OF THE CHINA RAILWAY SOCIETY. 2006 (6): 18-21.

[12] XIE Ruhe, QIU Zhuqiang, LI Qing-yun, WANG Rong-hua. The Application of Logit Model in Estimating the Mode Share of the Guangzhou-Shenzhen Railway [J]. China Railway SCIENCE. 2006 (5): 111-115.

[13] SHI Feng, DENG Lianbo, HUO Liang. Boarding Choice Behavior and Its Utility of Railway Passengers [J]. CHINA RAILWAY SCIENCE. 2007 (11): 117-121.

[14] Pawlak Z, Slowinski R., Rough set approach to multi-attribute decision analysis, European Journal of Operational Research (1994), p.443~459.

[15] Kryszkiewicz M., Comparative study of alternative types of knowledge reduction in insistent systems, International Journal of Intelligent Systems (2001).

[16] Xu Xi, Liu Yanbo, Fan Xuexin, Rough set data mining based on fuzzy toolbox and ROSETTA, Micro-computer Information(2007), pp.174-175.

[17] Zhang, Qi, Yang, Hao , Comprehensive evaluation of the degree of railway passenger satisfaction based on fuzzy factors, Tiedao Xuebao/Journal of the China Railway Society, February 2006 v 28, n 1, pp: 22-25.

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