A Trajectory Data Clustering Method Based On Dynamic Grid Density
نویسندگان
چکیده
منابع مشابه
A Trajectory Data Clustering Method Based On Dynamic Grid Density
Under the traditional method of frequent trajectory mining, the location of data is obtained through the GPS device. However, limited equipment accuracy may incur location ambiguity. In this paper, we propose a new trajectory data clustering method based on dynamic grid density, in order to remove this ambiguity. In this method, the trajectory space of an object is firstly divided into equal-si...
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Clustering analysis is one of the most important issues in trajectory data mining. Trajectory clustering can be widely applied in the detection of hotspots, mobile pattern analysis, urban transportation control, and hurricane prediction, etc. To obtain good clustering performance, the existing trajectory clustering approaches need to input one or more parameters to calibrate the optimal values,...
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To solve the problem of user trajectory prediction in the mobile communication environment, we proposed a self-adaptive trajectory prediction method (ATPDC) based on density clustering. And it consists of two stages which are trajectory modeling stage and trajectory updating stage respectively. In the first stage, it constructs the user trajectory prediction model by clustering historical traje...
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ژورنال
عنوان ژورنال: International Journal of Grid and Distributed Computing
سال: 2015
ISSN: 2005-4262,2005-4262
DOI: 10.14257/ijgdc.2015.8.2.01