Decision Support Technology Research of Emergency Disposal


This paper focuses on the problem about how to efficiently process the emergency of rail transit and guarantee the lowest accident loss in a short period of time, which is the urban rail transit management policy that makers are faced with, and which develops a high integrated system with strong information based on contingency plans to give the decision aid of urban rail transit emergency events. The paper uses formal methods to present the emergency plan, generate the emergency disposal plan, meet the requirements of on-site emergency disposal, and it realizes the modernization of urban rail transit emergency management which has an important significance. Finally, taking a subway fire as an example, it describes the practicality of the auxiliary decision system.

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Q. Wang, Y. Huang, Y. He, Z. Liu, H. Hu and A. Sun, "Decision Support Technology Research of Emergency Disposal," American Journal of Industrial and Business Management, Vol. 3 No. 8, 2013, pp. 740-745. doi: 10.4236/ajibm.2013.38084.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Z. Z. Wu and M. Liu, “Major Accident Emergency Rescue System and Plan the Introduction,” Metallurgical Industry Press, Beijing, 2003, pp. 1-5.
[2] “National Disposal of City Subway Accident Disaster Emergency Plan,” Policies and Documents, The State Council Issued in January 8, 2006.
[3] Y. P. Cui, Z. M. Tang and X. Wu, “System Research. Emergency Handling of Metro Accidents Based on Multi-Agent,” Journal of the China Railway Society, Vol. 26, No. 3, 2004, pp. 8-12.
[4] W. J. Li, Y. Qin and L. M. Jia, “Design and Implementation of Gateway of City Railway Transportation Emergency Management System,” 2007 3rd China Intelligent Transports Annual Conference, Nanjing, 15 December 2007, pp. 67-97.
[5] H. S. Zhu, “Thinking of Shanghai City Rail Transit Network Operation Management,” Modern City Rail Transportation, Vol. 4, 2007, pp. 10-13.
[6] Z. Q. Wang, M. Zhang and H. Xu, “Emergency Treatment Assistant Decision System of Urban Rail Transit,” International Conference on Transportation Engineering, Vol. 14, 2007, pp. 3707-3712.
[7] Y. J. He, “Individual Business Process Model,” Journal of Shandong University, 2008.
[8] “Digital Plan Template and Template Digital Alarm Information Report,” Beijing Jiaotong University, Beijing, 2012.
[9] S. J. Gu, X. D. Gao and R. Sun, “An Improved CBR Case Retrieval Similarity Measure Model,” Chinese Journal of Management Information, Vol. 14, No. 9, 2011, pp. 50-55.
[10] Z. L. Liao, X. W. Mao, Y. H. Liu, Z. X. Xu and P. M. Hannam, “CBR Respond and Preparedness System Development for Environmental Emergency,” Civil Engineering and Environmental Systems, Vol. 28, No. 4, 2011, pp. 301-323.
[11] D. Wettschereck, D. W. Aha and T. Mohri, “A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms,” Artificial Intelligence Review, Vol. 11, No. 1-5, 1997, pp. 273-314.

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