Sentence examples for trajectory cluster from inspiring English sources

Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution.

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set.

Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

Size trajectory clusters were chosen as best representing the dataset when using the 'Euclid' method within the cluster function (Figure S4).

The percentages assigned from these maps to each trajectory step allow a 'spectrum' of sea ice concentration of 5% width from 0 to 100% to be calculated for each of the trajectory clusters.

In the process of extracting STMS, a novel encoding method for trajectory clustering is proposed.

Wang et al. [16] propose a trajectory similarity measure to cluster the trajectories and then learn the scene model from trajectory clusters.

The above results indicate that the transformed trajectories are orders of magnitude safer than the original data in a measurable sense: but are they still useful to achieve the desired result, i.e., discovering trajectory clusters?

In this paper, our goal is to learn discriminative spatio-temporal trajectory clusters from a video that are most relevant to a specific type of action and to encode the trajectory as motion skeleton for each action class.

In the study by Dunn, Jordan, Mancl, Drangsholt and Resche [33], different trajectory clusters of facial, back, and abdominal pain as well as headache in adolescents between 11 and 14 years (n = 1 136) were examined.

Now, assume that one wants to discover the trajectory clusters emerging from the data through data mining, i.e., the groups of trajectories sharing common mobility behavior, such as the commuters following similar routes in their home-work and work-home trips.