K-Means　clustering　algorithm　attracts　increasing　focus　in　recent　years.　A　pending　problem　of　K-Means　clustering　algorithm　is　that　the　performance　is　affected　by　the　original　cluster　centers.　In　this　paper　the　K-Means　algorithm　is　improved　by　particle　swarm　optimization　and　the　initial　cluster　centers　are　generated　by　particle　swarm　optimization.The　experiments　and　comparisons　with　the　classical　K-Means　algorithm　indicate　that　the　improved　k-mean　clustering　algorithm　has　obvious　advantages　on　execution　time.　©　2014　Springer-Verlag　Berlin　Heidelberg.