Research Article
Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence
Algorithm 1
Ant colony optimization algorithm.
For every item do | Place randomly on grid | End For | For all ants do | Place ant at randomly selected site | End For | For to do | For all ants do | If ((ant Unladed) & (site occupied by item )) then | Compute the similarity of in | Calculate the and generate a random number | If then | Pick up item | Takes the and current position | Move the ant with the item to random site. | Else | Move the empty ant to random site | End If | Else if ((agent carrying) and (site empty)) then | Compute the similarity of | Calculate the and generate a random number | If then | Drop item | End If | Else | Move to a randomly selected neighboring site | End If | End For | If and (if attains radius change condition)) then | Reduce the radius | Clusters are generated iteratively and cluster centers are calculated | Connect the obtained clusters with the same cluster center | With Poor Similarity Relocate the Items | End If | End For | Print location of items. |
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