Metaheuristic Clustering

Cluster analysis means the organization of an unlabeled collection of objects into separate groups based on their similarity. With the use of several real world examples, this book formulates clustering as an optimization problem.

Latest research on metaheuristic clustering

Autorentext
Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

Inhalt
Metaheuristic Pattern Clustering An Overview.- Differential Evolution Algorithm: Foundations and Perspectives.- Modeling and Analysis of the Population-Dynamics of Differential Evolution Algorithm.- Automatic Hard Clustering Using Improved Differential Evolution Algorithm.- Fuzzy Clustering in the Kernel-Induced Feature Space Using Differential Evolution Algorithm.- Clustering Using Multi-objective Differential Evolution Algorithms.- Conclusions and Future Research.