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The paper proposed a novel ant colony optimization (ACO) and quantum particle swarm optimization (QPSO) method for spatial clustering with obstacles constraints (SCOC). We first developed AQPGSOD using ACO and QPSO based on grid model to obtain obstructed distance, and then we presented a new QPKSCOC based on QPSO and K-Medoids to cluster spatial data with obstacles. The experimental results show...
Spatial clustering has been an active research area in the data mining community. Spatial clustering is not only an important effective method but also a prelude of other task for spatial data mining (SDM). In this paper, we propose an improved ant colony optimization (IACO) and quantum particle swarm optimization (QPSO) method for spatial clustering with obstacles constraints (SCOC). In the process...
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