About this Journal Submit a Manuscript Table of Contents
Discrete Dynamics in Nature and Society
Volume 2014 (2014), Article ID 682147, 9 pages
http://dx.doi.org/10.1155/2014/682147
Research Article

Rough Set Approach for Group Evacuation Behavior Analysis in Passenger Transport Hub Area

1School of Transportation, Wuhan University of Technology, Wuhan, Hubei 430063, China
2Engineering Research Center for Transportation Safety (Ministry of Education), Wuhan University of Technology, Wuhan, Hubei 430063, China

Received 3 November 2013; Revised 27 February 2014; Accepted 2 March 2014; Published 17 April 2014

Academic Editor: Huimin Niu

Copyright © 2014 Peng Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. K. Lindell, J.-C. Lu, and C. S. Prater, “Household decision making and evacuation in response to Hurricane Lili,” Natural Hazards Review, vol. 6, no. 4, pp. 171–179, 2005. View at Publisher · View at Google Scholar · View at Scopus
  2. N. Dash and H. Gladwin, “Evacuation decision making and behavioral responses: individual and household,” Natural Hazards Review, vol. 8, no. 3, pp. 69–77, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Czajkowski, “Is it time to go yet? Understanding household hurricane evacuation decisions from a dynamic perspective,” Natural Hazards Review, vol. 12, no. 2, pp. 72–84, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Hasan, S. Ukkusuri, H. Gladwin, and P. Murray-Tuite, “Behavioral model to understand household-level hurricane evacuation decision making,” Journal of Transportation Engineering, vol. 137, no. 5, pp. 341–348, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. M. K. Lindell, J. E. Kang, and C. S. Prater, “The logistics of household hurricane evacuation,” Natural Hazards, vol. 58, no. 3, pp. 1093–1109, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. R. Mesa-Arango, S. Hasan, S. V. Ukkusuri, and P. Murray-Tuite, “Household-Level model for hurricane evacuation destination type choice using hurricane ivan data,” Natural Hazards Review, vol. 14, no. 1, pp. 11–20, 2013. View at Publisher · View at Google Scholar
  7. S. M. Lo, M. Liu, P. H. Zhang, and R. K. K. Yuen, “An artificial neural-network based predictive model for pre-evacuation human response in domestic building fire,” Fire Technology, vol. 45, no. 4, pp. 431–449, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. C. M. Zhao, S. M. Lo, S. P. Zhang, and M. Liu, “A post-fire survey on the pre-evacuation human behavior,” Fire Technology, vol. 45, no. 1, pp. 71–95, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. H. Fu and C. G. Wilmot, “Sequential logit dynamic travel demand model for hurricane evacuation,” Transportation Research Record, no. 1882, pp. 19–26, 2004. View at Scopus
  10. Y. Hsu and S. Peeta, “An aggregate approach to model evacuee behavior for no-notice evacuation operations,” Transportation, vol. 40, no. 3, pp. 671–696, 2013. View at Publisher · View at Google Scholar
  11. Z. Pawlak, “Rough sets,” International Journal of Computer and Information Sciences, vol. 11, no. 5, pp. 341–356, 1982. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  12. P. Sawicki and J. Zak, “Technical diagnostic of a fleet of vehicles using rough set theory,” European Journal of Operational Research, vol. 193, no. 3, pp. 891–903, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. J.-Y. Shyng, H.-M. Shieh, G.-H. Tzeng, and S.-H. Hsieh, “Using FSBT technique with Rough Set Theory for personal investment portfolio analysis,” European Journal of Operational Research, vol. 201, no. 2, pp. 601–607, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. L.-Y. Zhai, L.-P. Khoo, and S.-C. Fok, “Feature extraction using rough set theory and genetic algorithms—an application for the simplification of product quality evaluation,” Computers and Industrial Engineering, vol. 43, no. 4, pp. 661–676, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. R. Jensen and Q. Shen, “Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches,” IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 12, pp. 1457–1471, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. X. Wang, J. Yang, X. Teng, W. Xia, and R. Jensen, “Feature selection based on rough sets and particle swarm optimization,” Pattern Recognition Letters, vol. 28, no. 4, pp. 459–471, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. A.-R. Hedar, J. Wang, and M. Fukushima, “Tabu search for attribute reduction in rough set theory,” Soft Computing, vol. 12, no. 9, pp. 909–918, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. A.-E. Hassanien, “Rough set approach for attribute reduction and rule generation: a case of patients with suspected breast cancer,” Journal of the American Society for Information Science and Technology, vol. 55, no. 11, pp. 954–962, 2004. View at Publisher · View at Google Scholar · View at Scopus
  19. X. Bai, M. Zhang, Y. Qiu, and Q. Wu, “Algorithm for decision rules reduction in incomplete information system based on binary discemibility matrix,” in Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA '09), pp. 4061–4066, August 2009. View at Publisher · View at Google Scholar · View at Scopus
  20. L. Zhang, X. Lu, H. Wu, and S. Hao, “Improved heuristic algorithm used in attribute value reduction of rough set,” Chinese Journal of Scientific Instrument, vol. 30, no. 1, pp. 82–85, 2009. View at Scopus
  21. J. Liang, J. Wang, and Y. Qian, “A new measure of uncertainty based on knowledge granulation for rough sets,” Information Sciences, vol. 179, no. 4, pp. 458–470, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  22. E. Rolland, D. A. Schilling, and J. R. Current, “An efficient tabu search procedure for the p-Median Problem,” European Journal of Operational Research, vol. 96, no. 2, pp. 329–342, 1997. View at Scopus
  23. P. Yin and Y. Guo, “Optimization of multi-criteria website structure based on enhanced tabu search and web usage mining,” Applied Mathematics and Computation, vol. 219, no. 24, pp. 11082–11095, 2013. View at Publisher · View at Google Scholar
  24. Q. Wu and J.-K. Hao, “An adaptive multistart tabu search approach to solve the maximum clique problem,” Journal of Combinatorial Optimization, vol. 26, no. 1, pp. 86–108, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  25. Q. Feng, D. Miao, and Y. Cheng, “An approach to knowledge reduction based on relative partition granularity,” in Proceedings of the IEEE International Conference on Granular Computing (GRC '08), pp. 226–231, August 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. F. Glover, “Future paths for integer programming and links to artificial intelligence,” Computers & Operations Research, vol. 13, no. 5, pp. 533–549, 1986. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  27. C. Xie and M. A. Turnquist, “Lane-based evacuation network optimization: an integrated Lagrangian relaxation and tabu search approach,” Transportation Research C: Emerging Technologies, vol. 19, no. 1, pp. 40–63, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. P. A. Berger, “Rough set rule induction for suitability assessment,” Environmental Management, vol. 34, no. 4, pp. 546–558, 2004. View at Publisher · View at Google Scholar · View at Scopus
  29. C. K. Y. Lin and R. C. W. Kwok, “Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data and simulated data,” European Journal of Operational Research, vol. 175, no. 3, pp. 1833–1849, 2006. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Xu, S. Y. Chiu, and F. Glover, “Fine-tuning a tabu search algorithm with statistical tests,” International Transactions in Operational Research, vol. 5, no. 3, pp. 233–244, 1998. View at Publisher · View at Google Scholar
  31. G. H. Bham, B. S. Javvadi, and U. R. R. Manepalli, “Multinomial logistic regression model for Single-Vehicle and multivehicle collisions on urban u.s. Highways in arkansas,” Journal of Transportation Engineering-Asce, vol. 138, no. 6, pp. 786–797, 2012. View at Publisher · View at Google Scholar