Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013, Article ID 309750, 8 pages
http://dx.doi.org/10.1155/2013/309750
Research Article

The Evaluation of Dynamic Airport Competitiveness Based on IDCQGA-BP Algorithm

1Transportation Management College, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, China
2Faculty of Management and Economics, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, China

Received 25 August 2013; Accepted 30 November 2013

Academic Editor: Daoyi Dong

Copyright © 2013 Qiang Cui 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. R. Lieshout and H. Matsumoto, “New international services and the competitiveness of Tokyo International Airport,” Journal of Transport Geography, vol. 22, pp. 53–64, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. Y. Park, “An analysis for the competitive strength of Asian major airports,” Journal of Air Transport Management, vol. 9, no. 6, pp. 353–360, 2003. View at Publisher · View at Google Scholar · View at Scopus
  3. H. Lee and H. M. Yang, “Strategies for a global logistics and economic hub: Incheon International Airport,” Journal of Air Transport Management, vol. 9, no. 2, pp. 113–121, 2003. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Park, “Application of a fuzzy linguistic approach to analyse Asian airports' competitiveness,” Transportation Planning and Technology, vol. 20, no. 4, pp. 291–309, 1997. View at Google Scholar · View at Scopus
  5. C.-H. Yeh, Y.-L. Kuo, and Y.-H. Chang, “Fuzzy multiattribute evaluation of airport performance,” in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ '11), pp. 2630–2637, June 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. J. L. Peng and C. X. Zhan, “A case study on evaluation of airport logistics competitiveness based on AHP,” Advanced Materials Research, vol. 159, pp. 307–312, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Y. Wu and K. Y. Wu, “Study on the competency of Shanghai Pudong Airport in Asia-Pacific Ocean with AHP,” Logistics Technology, vol. 9, pp. 203–206, 2005. View at Google Scholar
  8. C. Cheng, K. S. Li, and R. Liu, “Research on the elements and enhancement measures of airport competitiveness: the case of Guangzhou Baiyun International Airport,” Industrial & Science Tribune, vol. 11, no. 2, pp. 24–25, 2012. View at Google Scholar
  9. Q. Cui, H. B. Kuang, C. Y. Wu, and Y. Li, “Dynamic formation mechanism of airport competitiveness: the case of China,” Transportation Research A, vol. 47, no. 1, pp. 10–18, 2013. View at Google Scholar
  10. S. Garelli, Top Class Competitors, Orient Press, Beijing, China, 2008.
  11. P. F. Ni, Chinese City Competitiveness Blue Book 2010: China City Competitiveness Report, Social Sciences Documentation Publishing House, Beijing, China, 2010.
  12. W. Wu, Neural Network Computation, Higher Education Press, Beijing, China, 2007.
  13. FECIT Technological Product Research Center, Neural Network Theory and MATLAB 7 Application, Publishing House of Electronics Industry, Beijing, China, 2005.
  14. R. P. Feynman, “Simulating physics with computers,” International Journal of Theoretical Physics, vol. 21, no. 6-7, pp. 467–488, 1982. View at Publisher · View at Google Scholar · View at MathSciNet
  15. K.-H. Han and J.-H. Kim, “Quantum-inspired evolutionary algorithm for a class of combinatorial optimization,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 6, pp. 580–593, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. S. Y. Li and P. C. Li, Quantum Computation and Quantum Optimization Algorithms, Harbin Institute of Technology Press, Harbin, China, 2009.
  17. M. X. Sun and X. P. Chen, “A immune algorithm based on the vector distance applied to function optimization,” Journal of Suzhou University Engineering Science Edition, vol. 30, no. 3, pp. 56–57, 2010. View at Google Scholar
  18. B. Wang, Z. Zhang, F. Li, Y. Sun, and H. Ding, “Comprehensive evaluation of regulated deficit irrigation using projection pursuit model based on improved double chains quantum genetic algorithm,” Transactions of the Chinese Society of Agricultural Engineering, vol. 28, no. 2, pp. 84–89, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. S. Qiao and Z. H. Dong, “A method of choosing BP network's initial weights,” Journal of Northeast Normal University, vol. 36, no. 3, pp. 25–30, 2004. View at Google Scholar
  20. Q. Zuo, S. S. Ye, R. C. Guo, and H. Shi, “Using quantum genetic algorithm to improve BP learning algorithm,” Computer System & Applications, vol. 2009, no. 5, pp. 53–55, 2009. View at Google Scholar
  21. Y. G. Cai, M. J. Zhang, H. Cai, and Y. Zhang, “Hybrid chaotic quantum evolutionary algorithm,” Systems Engineering—Theory & Practice, vol. 32, no. 10, pp. 2207–2214, 2012. View at Google Scholar
  22. Y.-H. Li and Y.-P. Wang, “An effective hybrid quantum genetic algorithm,” Systems Engineering—Theory & Practice, vol. 26, no. 11, pp. 116–124, 2006. View at Google Scholar · View at Scopus
  23. Y. B. Yang and S. Zhong, “A classification of Chinese civil airports,” Airport, vol. 11, pp. 39–42, 2004. View at Google Scholar