Clustering analysis is the task of assigning a set of objects to groups such that objects in one
group or cluster are more similar to each other than to those in other clusters. Clustering …

Clustering is a useful technique to create different groups of objects on the basis of their
nature. Objects of same group are of similar in nature and differ to the objects of other …

Data clustering is one of the most popular techniques in data mining. It is a method of
grouping data into clusters, in which each cluster must have data of great similarity and high …

In this paper we have investigated the performance of PSO Particle Swarm Optimization
based clustering on few real world data sets and one artificial data set. The performances …

It is well known that k-means algorithm is one of the most widely used clustering techniques.
However, solutions of k-means algorithm depend on the initialization of cluster centers and …

Optimization based pattern discovery has emerged as an important field in knowledge
discovery and data mining (KDD), and has been used to enhance the efficiency and …

Particle Swarm Optimization (PSO) is a heuristic and population based optimization
algorithm. PSO can be used in clustering problems and dominates well known clustering …

Clustering is a popular data analysis and data mining technique, which is the unsupervised
classification of patterns into subsets. To overcome the shortcomings of traditional …

Data clustering is a popular approach for automatically finding classes, concepts, or groups
of patterns. Clustering aims at representing large datasets by a fewer number of prototypes …

Computational intelligence approaches to data clustering have been successful in
producing compact and well-separated clusters. In particular, particle swarm optimization …