Spatial clustering algorithm with obstacles constraints by quantum particle swarm optimization and K-Medoids

The classical K-Medoids algorithm is easily trapped into local extremum and is sensitive to initialization. After analyzed the existing algorithms of spatial clustering with obstacles constraints, the paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-M...

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Bibliographic Details

Published in:	2010 Second International Conference on Computational Intelligence and Natural Computing Vol. 2; pp. 105 - 108
Main Authors:	Yang Teng-Fei, Zhang Xue-Ping
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.09.2010
Subjects:	Algorithm design and analysis Clustering algorithms Convergence K-Medoids algorithm obstacle constraints Optimization Particle swarm optimization Partitioning algorithms QPSO algorithm spatial clustering Sun
ISBN:	9781424477050, 1424477050
Online Access:	Get full text
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