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Clustering Algorithms for Moving Object Shape and Time Constrains Basis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 82 - Number 1 |
| Year of Publication: 2013 |
| Authors: S. Santhosh Baboo, K. Tajudin |
10.5120/14082-2080
|
S. Santhosh Baboo, K. Tajudin . Clustering Algorithms for Moving Object Shape and Time Constrains Basis. International Journal of Computer Applications. 82, 1 ( November 2013), 33-38. DOI=10.5120/14082-2080
Abstract
Clustering moving object trajectory data is an appealing research direction to fulfil the needs of many applications. In general, clustering is defined as the division of data into groups of similar objects. Each group, called as cluster, consists of objects that are similar among themselves and dissimilar to objects of other groups . Here to consider the moving object for clustering. The first section describes different object to flow in different directions, the clustering technique cluster object not only to the direction, time consideration and also cover with similar shape of object within the cluster window moving position. The objects flow in different way, different speed and different shape. Here the position or location of clustering and moving object directions are considered. The second section deals with the maximum wind details are Hurricane/Tropical Data for Northern Indian Ocean. Here to concentrate the flow record of maximum wind time duration basis, starting from the year, 2001 to 2010, the maximum cyclone flow updated different duration i. e. ,on hourly basis. The databases keep all records of data, to apply the clustering of four ways. First timely basis with limitation, second time and wind range basis, third exact time basis and fourth time limit with exact wind range.
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