Heuristic Algorithm for High-Speed Clustering of Neighbor Vehicular Position Coordinate 


Vol. 39,  No. 4, pp. 343-350, Apr.  2014


PDF
  Abstract

Divisive hierarchical clustering algorithms iterate the process of decomposition and clustering data recursively. In each recursive call, data in each cluster are arbitrarily selected and thus, the total clustering time can be increased, which causes a problem that it is difficult to apply the process of clustering neighbor vehicular position data in vehicular localization. In this paper, we propose a new heuristic algorithm for speeding up the clustering time by eliminating randomness of the selected data in the process of generating the initial divisive clusters.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

Y. Choi, S. Yoo, S. Seo, "Heuristic Algorithm for High-Speed Clustering of Neighbor Vehicular Position Coordinate," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 4, pp. 343-350, 2014. DOI: .

[ACM Style]

Yoon-Ho Choi, Seung-Ho Yoo, and Seung-Woo Seo. 2014. Heuristic Algorithm for High-Speed Clustering of Neighbor Vehicular Position Coordinate. The Journal of Korean Institute of Communications and Information Sciences, 39, 4, (2014), 343-350. DOI: .

[KICS Style]

Yoon-Ho Choi, Seung-Ho Yoo, Seung-Woo Seo, "Heuristic Algorithm for High-Speed Clustering of Neighbor Vehicular Position Coordinate," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 4, pp. 343-350, 4. 2014.