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
Diversity and adaptation in populations of clustering ants
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Future Generation Computer Systems
A novel ant-based clustering algorithm using the kernel method
Information Sciences: an International Journal
A survey: hybrid evolutionary algorithms for cluster analysis
Artificial Intelligence Review
Topic discovery from document using ant-based clustering combination
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
A novel ant-based clustering algorithm using Renyi entropy
Applied Soft Computing
Ant intelligence inspired blind data detection for ultra-wideband radar sensors
Information Sciences: an International Journal
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A modified clustering algorithm based on swarm intelligence (MSIC) is proposed in this paper.To improve the running efficiency of the SIC algorithm, the random projection of the patterns into the plane is modified. The patterns are firstly analyzed by principal component analysis (PCA) and the first two principal components (PCs) are retained. The patterns are projected into the plane according to their corresponding PCs, which are processed as the projection coordinates. This modification ensures that the pattern will be similar to the ones in its local surroundings and the rough clustering has been formed at the beginning time of the algorithm. Moreover, to reduce the influence of the parameters on the algorithm, a simple way to calculate the swarm similarity of the pattern is presented. The adjusting formula of the similarity threshold is also proposed. Finally, the modified algorithm is compared with the original one and the results prove the efficiency has been improved significantly.