Analysis and detection in V-formations with outliers (2014)
ABSTRACT: A diversity of movement patterns may be identified when studying a set of moving entities. One of these patterns is called V-formation since its shape resembles such letter. Informally, a set of entities shows a V-formation if they are located in one of its two characteristic lines. In this paper, we propose a model for identifying V-formations with outliers in a list of moving entities. An outlier is an entity of the formation that is apart from its characteristic lines. We present the formal rules of our model and an algorithm for detecting outliers. Our model was validated in NetLogo, a programming and modeling environment for simulating natural and social phenomena.