计算机技术与发展2016，Vol.26Issue(9)：178-182,5.DOI:10.3969/j.issn.1673-629X.2016.09.040
基于PSO的云计算环境中大数据优化聚类算法
Big Data Optimization Clustering Algorithm Based on PSO in Cloud Computing Environment
摘要
Abstract
In the cloud computing environment,the optimization of big data is the basis for the data optimized access and mining. In the traditional method,the fuzzy C means clustering algorithm is used to cluster the big data in the cloud computing,which is easy to fall into local extremum. A big data clustering algorithm based on Particle Swarm Optimization ( PSO) is proposed. The big data structure model in cloud computing environment is analyzed,and the discrete sample spectrum characteristics of big data are calculated,realizing feature extraction and information model construction of clustering sample. The particles are often fallen into local extremum in searching. The chaotic mapping is used to take the particles against the local extremum. The PSO is designed to carry on the feature clustering for the purpose of optimization clustering for big data. Simulation shows that the proposed algorithm is used for data clustering,and the error rate is reduced,and the optimization performance is better,and it has good application value.关键词
粒子群/数据聚类/云计算/大数据Key words
particle swarm/data clustering/cloud computing/big data分类
信息技术与安全科学引用本文复制引用
朱亚东,高翠芳..基于PSO的云计算环境中大数据优化聚类算法[J].计算机技术与发展,2016,26(9):178-182,5.基金项目
国家自然科学基金青年基金(61402202) （61402202）
