Automatic Generation Cloud Optimiz ation Based on Genetic Algorithm
DUAN Guiqin
Abstract：Aiming at solving the problem of clustering results randomness ,low stability ,easy to fall into local optimum and no global optimal solution of K‐means algorithm randomly chosen initial cluster centers ,a kind of initial cluster center optimization K‐means algorithm based on the product of the mean and maximum distance is put forward .Firstly ,the farthest distance mean sample set of data objects are chosen to join the cluster center set ,then the sample mean and maximum current cluster center product data object are set in turn to join the cluster center collection .Experimental results on the standard da‐ta sets show that ,compared with the original K‐means algorithm and another improved algorithm ,the proposed new cluste‐ring algorithm has a higher accuracy rate .
Keywords：K-means clustering algorithmmeanmaximum distance productdata mining
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 379-382 )