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Article overview
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Detecting Evidence of Organization in groups by Trajectories | | T. F. Silva
; J. E. B. Maia
; | | Date: |
1 Sep 2023 | | Abstract: | Effective detection of organizations is essential for fighting crime and
maintaining public safety, especially considering the limited human resources
and tools to deal with each group that exhibits co-movement patterns. This
paper focuses on solving the Network Structure Inference (NSI) challenge. Thus,
we introduce two new approaches to detect network structure inferences based on
agent trajectories. The first approach is based on the evaluation of graph
entropy, while the second considers the quality of clustering indices. To
evaluate the effectiveness of the new approaches, we conducted experiments
using four scenario simulations based on the animal kingdom, available on the
NetLogo platform: Ants, Wolf Sheep Predation, Flocking, and Ant Adaptation.
Furthermore, we compare the results obtained with those of an approach
previously proposed in the literature, applying all methods to simulations of
the NetLogo platform. The results demonstrate that our new detection approaches
can more clearly identify the inferences of organizations or networks in the
simulated scenarios. | | Source: | arXiv, 2309.00172 | | Services: | Forum | Review | PDF | Favorites | |
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