A Document of Ant Clustering By the Result of Topographic Mapping Intention

The clustering and topographic mapping is a motivated model for explaining two types of developing behavior observed in real ant colonies. Existing work demonstrated some promising characteristics of the heuristic but did not extend to a rigorous investigation of its capabilities. We are using an Improved Technique called ATTA includes adaptive, heterogeneous ants, a time-dependent transporting activity, and a method that transforms the spatial embedding produced by the algorithm into an clear partitioning. ATTA is then subjected to the most painstaking experimental evaluation of an ant-based clustering and sorting algorithm. In the case of antbased clustering and sorting, two related types of natural ant behavior are modeled. When clustering, ants gather items to form heaps. Its compare the performance to standard techniques for clustering and topographic mapping using a set of analytical evaluation functions and a range of synthetic and real data collections. It Return an explicit partitioning of data, which would allow clustering solutions to be evaluated without human intervention. It express the ability of ant-based clustering and sorting to automatically identify the number of clusters inherent to a data collection, and to produce high quality solutions .it is particularly robust for clusters of differing sizes , and overlapping clusters.