Title :
Ant colony clustering by expert ants
Author :
Sadeghi, Zahra ; Teshnehlab, Mohammad
Author_Institution :
Comput. Eng. Dept., Islamic Azad Univ.
Abstract :
In this article a new ant clustering algorithm based on case based reasoning (CBR) is presented. Every ant has a case base which is updated iteratively by the process of CBR. The ant which is successful in dropping an item becomes an expert and can use its knowledge for future picked up items. Also expert ants are capable of cooperating to share their knowledge for even better clustering. Our simulation results demonstrated better performance than previous approaches.
Keywords :
case-based reasoning; expert systems; optimisation; pattern clustering; unsupervised learning; CBR; ant colony clustering; case based reasoning; expert ant; knowledge sharing; optimisation; unsupervised learning; Ant colony optimization; Artificial intelligence; Clustering algorithms; Data engineering; Data mining; Iterative algorithms; Libraries; Particle swarm optimization; Robustness; Unsupervised learning; ant based clustering; ant colony optimization;
Conference_Titel :
Computer and Information Technology, 2008. ICCIT 2008. 11th International Conference on
Conference_Location :
Khulna
Print_ISBN :
978-1-4244-2135-0
Electronic_ISBN :
978-1-4244-2136-7
DOI :
10.1109/ICCITECHN.2008.4803115
