Title :
Clustering using chemical and colonial odors of real ants
Author :
Masmoudi, N. ; Azzag, Hanane ; Lebbah, Mustapha ; Bertelle, Cyrille
Author_Institution :
LITIS, Univ. of Havre, France
Abstract :
We suggest in this paper a new automatic data clustering model based on the behavior of real ants. Drawing on a simulation of colonial odors and pheromone mechanisms, we set up complete dynamic graphs to solve the problem of data clustering. Using graph we will clarify the relationships between clusters of data.
Keywords :
chemical engineering computing; data mining; digital simulation; graph theory; pattern clustering; automatic data clustering model; chemical odors; colonial odors; complete dynamic graphs; data mining; pheromone mechanisms; real ants; Classification algorithms; Ants behavior; Clustering; Data analysis; Swarm intelligence;
Conference_Titel :
Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress on
Conference_Location :
Fargo, ND
Print_ISBN :
978-1-4799-1414-2
DOI :
10.1109/NaBIC.2013.6617863
