Abstract

Mohammed A. Abo Rezka
Hybrid ant-based clustering algorithm with cluster analysis techniques
A hybrid ant-based clustering algorithm is introduced to improve ants’ decisions, picking up and ping off data objects. The goal is to useful information collected from environment to contribute to solving cluster problems of assigning scattered data objects to homogeneous clusters. The proposed algorithm is based on a combination of robust methods inspired from ACC, AHC and DBSCAN algorithms.The proposed algorithm does not need prior datasets knowledge their cluster numbers, unlike the K-means algorithm.