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Mathematical Problems in Engineering
Volume 2013, Article ID 980154, 11 pages
http://dx.doi.org/10.1155/2013/980154
Research Article

A Nonlinear Optimization Technique of Tunnel Construction Based on DE and LSSVM

1School of Resources & Civil Engineering, Northeastern University, Shenyang 110004, China
2Highway and Bridge Engineering Institute, Dalian Maritime University, Dalian 116026, China

Received 22 November 2012; Revised 10 February 2013; Accepted 23 February 2013

Academic Editor: Shengyong Chen

Copyright © 2013 Xing Jun 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. S. Sakurai and K. Takeuchi, “Back analysis of measured displacements of tunnels,” Rock Mechanics and Rock Engineering, vol. 16, no. 3, pp. 173–180, 1983. View at Publisher · View at Google Scholar · View at Scopus
  2. H. Mashimo, “State of the road tunnel safety technology in Japan,” Tunnelling and Underground Space Technology, vol. 17, no. 2, pp. 145–152, 2002. View at Publisher · View at Google Scholar · View at Scopus
  3. S. H. Li, New Theory of Tunnel Supporting: The Application and Theory of Typical Similar Supporting Design, China Science Press, Beijing, China, 1999.
  4. W. S. Zhu and M. C. He, Surrounding Rock Stability of Complex Condition and Rock Mass Dynamic Construction Mechanics, China Science Press, Beijing, China, 1995.
  5. B. J. Arends, S. N. Jonkman, J. K. Vrijling, and P. H. A. J. M. van Gelder, “Evaluation of tunnel safety: towards an economic safety optimum,” Reliability Engineering and System Safety, vol. 90, no. 2-3, pp. 217–228, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Pérez-Romero, C. S. Oteo, and P. de la Fuente, “Design and optimisation of the lining of a tunnel in the presence of expansive clay levels,” Tunnelling and Underground Space Technology, vol. 22, no. 1, pp. 10–22, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. G. Tang and G. T. C. Kung, “Application of nonlinear optimization technique to back analyses of deep excavation,” Computers and Geotechnics, vol. 36, no. 1-2, pp. 276–290, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. M. A. Hashash, S. Levasseur, A. Osouli, R. Finno, and Y. Malecot, “Comparison of two inverse analysis techniques for learning deep excavation response,” Computers and Geotechnics, vol. 37, no. 3, pp. 323–333, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. S. C. Lim, C. H. Eab, K. H. Mak, M. Li, and S. Y. Chen, “Solving linear coupled fractional differential equations by direct operational method and some applications,” Mathematical Problems in Engineering, vol. 2012, Article ID 653939, 28 pages, 2012. View at Publisher · View at Google Scholar · View at MathSciNet
  10. H. L. Liu, P. Li, and J. Y. Liu, “Numerical investigation of underlying tunnel heave during a new tunnel construction,” Tunnelling and Underground Space Technology, vol. 26, no. 2, pp. 276–283, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. F. S. Zhang, X. X. Xie, and H. W. Huang, “Application of ground penetrating radar in grouting evaluation for shield tunnel construction,” Tunnelling and Underground Space Technology, vol. 25, no. 2, pp. 99–107, 2010. View at Publisher · View at Google Scholar · View at Scopus
  12. Y. Xu, X. Y. Chen, and Q. H. Li, “INS/WSN-integrated navigation utilizing LSSVM and H filtering,” Mathematical Problems in Engineering, vol. 2012, Article ID 707326, 19 pages, 2012. View at Publisher · View at Google Scholar
  13. P. Z. Lu, S. C. Chen, and Y. J. Zheng, “Artificial intelligence in civil engineering,” Mathematical Problems in Engineering, vol. 2012, Article ID 145974, 22 pages, 2012. View at Publisher · View at Google Scholar
  14. C. Carlo, S. Y. Chen, and A. Gani, “Information and modeling in complexity,” Mathematical Problems in Engineering, vol. 2012, Article ID 868413, 4 pages, 2012. View at Publisher · View at Google Scholar
  15. X. T. Feng, Z. Zhang, and Q. Sheng, “Estimating mechanical rock mass parameters relating to the Three Gorges Project permanent shiplock using an intelligent displacement back analysis method,” International Journal of Rock Mechanics and Mining Sciences, vol. 37, no. 7, pp. 1039–1054, 2000. View at Publisher · View at Google Scholar · View at Scopus
  16. A. N. Jiang, “Forecasting nonlinear time series of surrounding rock deformations of underground cavern based on PSO-SVM,” Rock and Soil Mechanics, vol. 28, no. 6, pp. 1176–1180, 2007 (Chinese). View at Google Scholar · View at Scopus
  17. A. N. Jiang, S. Y. Wang, and S. L. Tang, “Feedback analysis of tunnel construction using a hybrid arithmetic based on Support Vector Machine and Particle Swarm Optimisation,” Automation in Construction, vol. 20, no. 4, pp. 482–489, 2011. View at Publisher · View at Google Scholar · View at Scopus
  18. V. N. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, NY, USA, 1995. View at MathSciNet
  19. J. A. K. Suykens, T. van Gestel, and J. de Brabanter, Least Squares Support Vector Machines, World Scientific, Singapore, 2002.
  20. J. A. K. Suykens and J. Vandewalle, “Least squares support vector machine classifiers,” Neural Processing Letters, vol. 9, no. 3, pp. 293–300, 1999. View at Publisher · View at Google Scholar · View at Scopus
  21. R. Storn and K. Price, “Differential evolution,” 2008, http://www1.icsi.berkeley.edu/~storn/code.html.
  22. A. W. Mohamed, H. Z. Sabry, and M. Khorshid, “An alternative differential evolution algorithm for global optimization,” Journal of Advanced Research, vol. 3, no. 2, pp. 149–165, 2012. View at Publisher · View at Google Scholar
  23. J. Ilonen, J. K. Kamarainen, and J. Lampinen, “Differential evolution training algorithm for feed-forward neural networks,” Neural Processing Letters, vol. 17, no. 1, pp. 93–105, 2003. View at Publisher · View at Google Scholar · View at Scopus