基于K-Means和网格化聚类的云数据管理模型研究

Research on Cloud Data Management Model Based K-Means and Gridding Clustering

针对云数据的分类具有模糊性、不确定性等特点,将K-Means聚类与网格化互联互通的思想运用到云数据管理的模型中,提出了一种"K-Means网格化的云数据管理模型"方法。通过随机产生的高斯分布数据表明:所提出模型不仅能高效地解决数据在分类、模糊性等方面存在的问题,而且在提高数据分布区域化精度的同时减少了数据管理的个数。利用Matlab工具对数据进行了K-Means网格化验证分析,分析结果能为企业的数据管理提供有益的借鉴。

According to that the cloud data classification has the characteristics of fuzziness and uncertainty,and K-Means clustering and grid interconnection thought is introduced into the Cloud Data Management（CDM） model,and a new method ＂Cloud Data Management model based on KMeans Grid＂ is proposed in this paper.The demonstration shows that the present model not only is the more efficient solution to classification data,fuzzy and other characteristics,but also can improve the accuracy of regional data distribution while reducing the number of data management.Using MATLAB tools to verify and analyze data into K-Means grid,and the results of the analysis results can provide useful reference for company data management.