2014 | OriginalPaper | Buchkapitel
Data Clustering Using Particle Swarm Optimization
verfasst von : Mingru Zhao, Hengliang Tang, Jian Guo, Yuan Sun
Erschienen in: Future Information Technology
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
K-Means clustering algorithm attracts increasing focus in recent years. A pending problem of K-Means clustering algorithm is that the performance is affected by the original cluster centers. In this paper the K-Means algorithm is improved by particle swarm optimization and the initial cluster centers are generated by particle swarm optimization..The experiments and comparisons with the classical K-Means algorithm indicate that the improved k-mean clustering algorithm has obvious advantages on execution time.