Application of A SOM and K-Means Algorithm in Welding Quality in SMT
ZHANG Qiangwu
TANG Luxin
Abstract：As the high complexity and low precision of the SOM neural network algorithm and the shortcomings of the K-Means clustering algorithm needs to determine the number of clusters advanced and randomly select initial clustering cen-ters ,a SOM neural network combined with K-Means of S-K secondary clustering algorithm is proposed ,having complemen-tary function .If the algorithm is used in SMT soldering ,the precision of data clustering information can be enhanced .The intuitive vision of data distributioncould be got and the overall performance of the system is improved .
Keywords：SOM neural networkK-Means clusteringsurface mounting technologyweldquality
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1127-1130,1136 )