Adaptive Spatial Clustering for Multi-Dimensional Data and Its Cloud Model Representation - 文章详情页

作者：

Gao, Bin (Gao, Bin.) | Zhang, Xinhai (Zhang, Xinhai.) | Xu, Xiaobin (Xu, Xiaobin.) | Liu, Yifeng (Liu, Yifeng.)

收录：

摘要：

In　view　of　the　problem　that　the　number　of　clusters　need　to　be　set　manually,　it　is　difficult　to　process　the　multi-dimensional　data　effectively,　and　the　clustering　results　are　not　described　effectively　when　the　multi-dimensional　data　need　to　be　clustered.　This　paper　proposes　a　method　of　adaptive　spatial　clustering　and　its　cloud　model　representation　for　the　multi-dimensional　data.　This　method　can　be　used　to　cluster　multi-dimensional　spatial　data,　form　qualitative　description　of　clustering　results,　and　realize　the　reconstruction　and　verification　of　qualitative　description　features.　Through　simulation　experiments,　this　method　can　cluster　data　adaptively　without　the　need　to　set　the　number　of　clusters.　At　the　same　time,　it　has　a　good　ability　to　abstract　and　reconstruct　digital　features.　©　2020　ACM.

关键词：

Artificial intelligence Cloud computing Clustering algorithms

作者机构：

[ 1 ] [Gao, Bin]Beijing University of Technology, Future Network Innovation Center, China
[ 2 ] [Zhang, Xinhai]China Academy of Electronics and Information Technology, National Engineering Laboratory for Public, Safety Risk Perception and Control by Big Data, China
[ 3 ] [Xu, Xiaobin]Beijing University of Technology, Future Network Innovation Center, China
[ 4 ] [Liu, Yifeng]China Academy of Electronics and Information Technology, National Engineering Laboratory for Public, Safety Risk Perception and Control by Big Data, China

通讯作者信息：

电子邮件地址：

查看成果更多字段

成果类型
所属机构

所有年份指定年份从至