An improved K-Means algorithm based on bacterial foraging - 文章详情页

作者：

Zhao, Mingru (Zhao, Mingru.) | Ji, Junzhong (Ji, Junzhong.) (学者：冀俊忠) | Liu, Chunnian (Liu, Chunnian.) | Tang, Hengliang (Tang, Hengliang.)

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EI Scopus

摘要：

In　the　recent　years,　the　social　foraging　behavior　of　E.　coli　bacteria　in　human　intestine　has　been　used　to　solve　optimization　problems.　This　paper　presents　an　improved　K-Means　algorithm　involving　bacterial　foraging　in　order　to　overcome　the　defects　in　K-Means　algorithm.　The　paper　applied　both　the　new　clustering　algorithm　named　K-Means-BFA-K-Means　algorithm　(KBFAK)　and　the　elementary　K-Means　algorithm　to　the　fabric　data　items.　It　is　found　that　the　KBFAK　has　the　same　results　as　K-Means,　but　its　execution　time　has　been　largely　reduced.　©　2012　Praise　Worthy　Prize　S.r.l.　-　All　rights　reserved.

关键词：

Escherichia coli K-means clustering

作者机构：

[ 1 ] [Zhao, Mingru]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Zhao, Mingru]School of Information, Beijing Wuzi University, Beijing 101149, China
[ 3 ] [Ji, Junzhong]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Liu, Chunnian]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Tang, Hengliang]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 6 ] [Tang, Hengliang]School of Information, Beijing Wuzi University, Beijing 101149, China

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