Table of Contents Author Guidelines Submit a Manuscript
Table of Contents Alerts

To receive news and publication updates for Discrete Dynamics in Nature and Society, enter your email address in the box below.

Discrete Dynamics in Nature and Society
Volume 2018 (2018), Article ID 6848745, 15 pages
https://doi.org/10.1155/2018/6848745
Research Article

Prediction of Drifter Trajectory Using Evolutionary Computation

Yong-Wook Nam and Yong-Hyuk Kim

Department of Computer Science, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Republic of Korea

Correspondence should be addressed to Yong-Hyuk Kim; rk.ca.wk@ylfdhy

Received 11 September 2017; Revised 6 November 2017; Accepted 19 December 2017; Published 24 January 2018

Academic Editor: Alicia Cordero

Copyright © 2018 Yong-Wook Nam and Yong-Hyuk Kim. 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. T. M. Özgökmen, L. I. Piterbarg, A. J. Mariano, and E. H. Ryan, “Predictability of drifter trajectories in the tropical Pacific Ocean,” Journal of Physical Oceanography, vol. 31, no. 9, pp. 2691–2720, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. S. Castellari, A. Griffa, T. M. Özgökmen, and P.-M. Poulain, “Prediction of particle trajectories in the adriatic sea using Lagrangian data assimilation,” Journal of Marine Systems, vol. 29, no. 1-4, pp. 33–50, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. K. R. Thompson, J. Sheng, P. C. Smith, and L. Cong, “Prediction of surface currents and drifter trajectories on the inner Scotian shelf,” Journal of Geophysical Research: Oceans, vol. 108, no. 9, pp. 3–1, 2003. View at Google Scholar · View at Scopus
  4. C. D. Winant, D. J. Alden, E. P. Dever, K. A. Edwards, and M. C. Hendershott, “Near-surface trajectories off central and southern California,” Journal of Geophysical Research: Oceans, vol. 104, no. 7, Article ID 1999JC900083, pp. 15713–15726, 1999. View at Publisher · View at Google Scholar · View at Scopus
  5. The Global Drifter Program: What's a drifter?, http://www.aoml.noaa.gov/phod/dac/gdp_drifter.php. View at Publisher · View at Google Scholar
  6. ARA Consulting Technology, URL, http://www.aracnt.com/.
  7. Earth:: a global map of wind, weather and ocean condition, https://earth.nullschool.net/.
  8. OpenWeatherMap, https://openweathermap.org/api.
  9. https://www.nefsc.noaa.gov/press_release/2012/SciSpot/SS1211/.
  10. C. M. Allen, “Numerical simulation of contaminant dispersion in estuary flows,” Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol. 381, pp. 179–194. View at Publisher · View at Google Scholar
  11. C.-Y. Yang, Y.-F. Liaw, C.-M. Chu, and I.-S. Sheen, “White count, pH and lactate in ascites in the diagnosis of spontaneous bacterial peritonitis,” Hepatology, vol. 5, no. 1, pp. 85–90, 1985. View at Publisher · View at Google Scholar · View at Scopus
  12. K. Price, R. M. Storn, and J. A. Lampinen, Differential Evolution: a Practical Approach to Global Optimization, Springer Science & Business Media, 2006.
  13. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948. View at Scopus
  14. L. Lamberti, “An efficient simulated annealing algorithm for design optimization of truss structures,” Computers & Structures, vol. 86, no. 19-20, pp. 1936–1953, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. N. Hansen, S. D. Müller, and P. Koumoutsakos, “Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES),” Evolutionary Computation, vol. 11, no. 1, pp. 1–18, 2003. View at Publisher · View at Google Scholar · View at Scopus
  16. The CMA Evolution Strategy, https://www.lri.fr/~hansen/cmaesintro.html.
  17. Y. Liu, X. Yao, and T. Higuchi, “Evolutionary ensembles with negative correlation learning,” IEEE Transactions on Evolutionary Computation, vol. 4, no. 4, pp. 380–387, 2000. View at Publisher · View at Google Scholar · View at Scopus
  18. P. Refaeilzadeh, L. Tang, and H. Liu, “Cross-validation,” in Encyclopedia of Database Systems, pp. 532–538, Springer, USA, 2009. View at Google Scholar
  19. Y. Liu and R. H. Weisberg, “Evaluation of trajectory modeling in different dynamic regions using normalized cumulative Lagrangian separation,” Journal of Geophysical Research: Oceans, vol. 116, no. 9, Article ID C09013, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. R. Sorgente, C. Tedesco, F. Pessini et al., “Forecast of drifter trajectories using a Rapid Environmental Assessment based on CTD observations,” Deep-Sea Research Part II: Topical Studies in Oceanography, vol. 133, pp. 39–53, 2016. View at Publisher · View at Google Scholar · View at Scopus
  21. Y. Liu, R. H. Weisberg, S. Vignudelli, and G. T. Mitchum, “Evaluation of altimetry-derived surface current products using Lagrangian drifter trajectories in the eastern Gulf of Mexico,” Journal of Geophysical Research: Oceans, vol. 119, no. 5, pp. 2827–2842, 2014. View at Publisher · View at Google Scholar · View at Scopus
  22. Differential Evolution, http://www1.icsi.berkeley.edu/~storn/code.html. View at Publisher · View at Google Scholar
  23. CMA-ES Source Code, https://www.lri.fr/~hansen/cmaes_inmatlab.html.
  24. Particle Swarm Optimization (PSO) in C, https://github.com/kkentzo/pso.
  25. L. I. Kuncheva and J. J. Rodríguez, “A weighted voting framework for classifiers ensembles,” Knowledge and Information Systems, vol. 38, no. 2, pp. 259–275, 2014. View at Publisher · View at Google Scholar · View at Scopus