About this Journal Submit a Manuscript Table of Contents
The Scientific World Journal
Volume 2013 (2013), Article ID 160687, 8 pages
http://dx.doi.org/10.1155/2013/160687
Research Article

QPSO-Based Adaptive DNA Computing Algorithm

1Computer Engineering Department, Firat University, Elazig, Turkey
2Computer Programming Department, Gaziosmanpaşa University, Tokat, Turkey

Received 3 May 2013; Accepted 20 June 2013

Academic Editors: P. Agarwal and Y. Zhang

Copyright © 2013 Mehmet Karakose and Ugur Cigdem. 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. L. M. Adleman, “Molecular computation of solutions to combinatorial problems,” Science, vol. 266, no. 5187, pp. 1021–1024, 1994. View at Scopus
  2. R. J. Lipton, “Using DNA to solve NP-complete problems,” Science, vol. 268, no. 5210, pp. 542–545, 1995. View at Scopus
  3. C.-L. Lin, H.-Y. Jan, and T.-S. Hwang, “Structure variable PID control design based on DNA coding method,” in Proceedings of the IEEE International Symposium on Industrial Electronics (IEEE-ISlE '04), pp. 423–428, May 2004. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Ding and L. Ren, “DNA genetic algorithm for design of the generalized membership-type Takagi-Sugeno fuzzy control system,” in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, vol. 5, pp. 3862–3867, October 2000. View at Scopus
  5. J. J. Kim and J. J. Lee, “PID controller design using double helix structured DNA algorithms with a recovery function,” Artificial Life and Robotics, vol. 12, no. 1-2, pp. 241–244, 2008. View at Publisher · View at Google Scholar
  6. Y. Wang, G. Cui, and Z. Wang, “Research on DNA computer with coprocessor organizational model,” in Proceedings of the 8th International Conference on High-Performance Computing in Asia-Pacific Region (HPC Asia '05), vol. 6, pp. 544–549, December 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Zhang, Y. Niu, and Y. Wang, “DNA computing in microreactors: a solution to the minimum vertex cover problem,” in Proceedings of the 6th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA '11), pp. 236–240, September 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Sridhar and S. Balasubramaniam, “GIS integrated DNA computing for solving travelling salesman problem,” in Proceedings of the IEEE Symposium on Computers & Informatics (ISCI '11), pp. 402–406, mys, March 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. U. Çiğdem and M. Karaköse, “Using of DNA computing for tuning of parameters of PI and fuzzy controllers,” in Proceedings of the Automatic Control National Symposium, pp. 665–670, Izmir, Turkey, 2011.
  10. F. Li, Z. Li, and J. Xu, “DNA computing model based on photoelectric detection system with magnetic beads,” in Proceedings of the 6th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA '11), pp. 170–175, September 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Huang and L. He, “DNA computing research progress and application,” in Proceedings of the 6th International Conference on Computer Science and Education (ICCSE '11), pp. 232–235, August 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Xu, X. Qiang, Y. Yang et al., “An unenumerative DNA computing model for vertex coloring problem,” IEEE Transactions on Nanobioscience, vol. 10, no. 2, pp. 94–98, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. S. Mitra, R. Das, and Y. Hayashi, “Genetic networks and soft computing,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 1, pp. 94–107, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. H. Jiao, Y. Zhong, L. Zhang, and P. Li, “Unsupervised remote sensing image classification using an artificial DNA computing,” in Proceedings of the 2011 7th International Conference on Natural Computation (ICNC '11), pp. 1341–1345, July 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. Z. Yin, C. Hua, and B. Song, “Plasmid DNA computing model of 0-1 programming problem,” in Proceedings of the IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA '10), pp. 148–151, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Xu, X. Qiang, K. Zhang et al., “A parallel type of DNA computing model for graph vertex coloring problem,” in Proceedings of the IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA '10), pp. 231–235, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Huang, Z. Yin, and Y. Tian, “Design of PID controller based on DNA computing,” in Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence (AICI '10), pp. 195–198, October 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. Z. Yin, B. Song, C. Zhen, and C. Hua, “Molecular beacon-based DNA computing model for maximum independent set problem,” in Proceedings of the International Conference on Intelligent Computation Technology and Automation (ICICTA '10), pp. 732–735, May 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. C.-L. Lin, H.-Y. Jan, and T.-S. Hwang, “Structure variable PID control design based on DNA coding method,” in Proceedings of the IEEE International Symposium on Industrial Electronics, pp. 423–428, May 2004. View at Publisher · View at Google Scholar · View at Scopus
  20. C.-L. Lin, H.-Y. Jan, and T.-H. Huang, “Self-organizing PID control design based on DNA computing method,” in Proceedings of the IEEE International Conference on Control Applications, pp. 568–573, September 2004. View at Scopus
  21. C. V. Henkel, Experimental DNA computing [Ph.D. thesis], Leiden University, 2005.
  22. Z. F. Qiu, Advance the DNA computing [Ph.D. thesis], Texas A&M University, College Station, Tex, USA, 2003.
  23. M. O. Rahman, A. Hussain, E. Scavino, M. A. Hannan, and H. Basri, “Object identification using DNA computing algorithm,” in Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1–7, 2012. View at Publisher · View at Google Scholar
  24. J. M. Chaves-González and M. A. Vega-Rodríguez, “DNA sequence design for reliable DNA computing by using a multiobjective approach,” in Proceedings of the 13th IEEE International Symposium on Computational Intelligence and Informatics, pp. 73–79, 2012.
  25. H. Zhang and X. Liu, “A general object oriented description for DNA computing technique,” in Proceedings of the International Conference on Information Technology and Computer Science (ITCS '09), pp. 3–6, July 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. H. Jiao, Y. Zhong, and L. Zhang, “Artificial DNA computing-based spectral encoding and matching algorithm for hyperspectral remote sensing data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 10, pp. 4085–4105, 2012. View at Publisher · View at Google Scholar · View at Scopus
  27. W. Liu, S. Sun, and Y. Guo, “A DNA computing model of perceptron,” in Proceedings of the Pacific-Asia Conference on Circuits, Communications and System (PACCS '09), pp. 710–712, May 2009. View at Publisher · View at Google Scholar · View at Scopus
  28. Q. Zhang, X. Xue, and X. Wei, “A novel image encryption algorithm based on DNA subsequence operation,” The Scientific World Journal, vol. 2012, Article ID 286741, 10 pages, 2012. View at Publisher · View at Google Scholar
  29. J. Xu, X. Qiang, Y. Yang et al., “An unenumerative DNA computing model for vertex coloring problem,” IEEE Transactions on Nanobioscience, vol. 10, no. 2, pp. 94–98, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. M. Xi, J. Sun, and W. Xu, “Parameter optimization of PID controller based on Quantum-Behaved Particle Swarm Optimization Algorithm,” Complex Systems and Applications-Modelling, vol. 14, supplement 2, pp. 603–607, 2007.