Linear programming: methods and applications (5th ed.)
Linear programming: methods and applications (5th ed.)
The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Out of control: the new biology of machines, social systems, and the economic world
Out of control: the new biology of machines, social systems, and the economic world
The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Artificial Intelligence in Geography
Artificial Intelligence in Geography
Modeling Moving Objects over Multiple Granularities
Annals of Mathematics and Artificial Intelligence
Temporal Interpolation of Spatially Dynamic Object
Geoinformatica
Geographic Data Mining and Knowledge Discovery
Geographic Data Mining and Knowledge Discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient detection of motion patterns in spatio-temporal data sets
Proceedings of the 12th annual ACM international workshop on Geographic information systems
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Lacunarity analysis of raster datasets and 1D, 2D, and 3D point patterns
Computers & Geosciences
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Recent developments in sensing and tracking technologies have enabled large geographical databases to be established that represent spatial dynamics of 'behavioral entities'. Within this type of dynamics there are several levels and modes of organization that need to be revealed. Clusters are high-level groupings of entities, where change in their location and form, including split and merge events, represents self-organization and functioning patterns. Such information may contribute for better understanding spatially complex dynamic patterns. The main objective of this article is to develop an adaptable methodology that facilitates exploration of spatial order and processes in point pattern dynamics. The approach presented here utilizes data-clustering at each snapshot of the moving pattern, and then involves pairwise linking between the clusters identified at each snapshot and those identified in the following snapshot. Such linking is based on a new methodology that defines well globally optimized solutions for numerous possible linking combinations based on Linear Programming. A preliminary assessment of the approach was conducted with an existing Ants' simulation tool, capable of creating data sets covering in detail a substantial portion of the nest's life cycle.