Hybrid Particle Swarm Optimization for Data Clustering

Data Clustering is process of organizing data into specific groups, the characteristics of which are unknown. Data clustering has been studied for a long time by many researchers with different methods. Traditional clustering techniques has some drawbacks. In this book, we deals with such limitations of traditional clustering techniques. To overcome these drawback we have selected ¿Nature-Inspired / Swarm Intelligence' technique that is ¿Particle Swarm Optimization (PSO)¿ for data clustering. As we know, nature is always a source of inspiration. In last few decades, the research is stimulated on new computing paradigms and result of this effort is emergence of new problem solving techniques. These techniques are widely used due to their decentralized and self-organized behaviour.