options have been taken into consideration. By using a clustering algorithm for analyzing both the database containing events …

This paper review some state-of-the art non-parallel and parallel approaches of data clustering and present the … usefulness of parallel genetic algorithms (PGAs) for clustering. In solving the clustering problem many traditional methods stuck … general it is unknown to the user. Therefore, clustering becomes a trial-and-error work and is also very expensive in terms of …

, data mining method clustering was undertaken to identify the customersegments. Two different clustering methods were tested …

Clustering is applied in wireless sensor networks for increasing energy efficiency. Clustering methods in wireless … sensor networks are different from those in traditional data mining systems. This paper proposes a novel clustering algorithm … clustering in wireless sensor networks and several evaluation metrics are given. MSTME performs better than already known …

the variables are calculated, clustering methods (K-means and fuzzy K-means) are used to segment countries and compare the …

the variables are calculated, clustering methods (K-means and fuzzy K-means) are used to segment countries and compare the …