摘要
针对大数据下的人力流动区域的估算问题,提出基于大数据分析的人力流动区域估计仿真模型。引进了K近邻非参数估计仿真模型,对大数据背景下的人力流动区域进行标准估算。同时能够对K值进行预留计算,避免大数据干扰的发生,优化了分类近邻子集生成模块,有效地提高了估算能力以及估算的范围,对人力流动区域的估算准确性有极大的帮助。并进行实验分析,由实验分析可知,提出的方法能够准确地对人力流动的区域进行系统的估算。
In allusion to the estimation problem of human resource flow region under the background of big data, an estima- tion simulation model based on big data analysis is proposed for human resource flow region. The K-nearest neighbor nonparametric estimation simulation model is introduced to perform standard estimation of human resource flow region under the background of big data. The K value is reserved for calculation to avoid the occurrence of big data interference. The classified nearest neighbor subset generation module is optimized to effectively improve the estimation capability and estimation range, which is of great help to the estimation accuracy of human resource flow region. The experiment was carried out. The experimental analysis results show that the proposed simulation model can perform systematic estimation of human resource flow region accurately.
出处
《现代电子技术》
北大核心
2017年第24期74-76,共3页
Modern Electronics Technique
关键词
大数据分析
人力流动区域
估计模型仿真
K近邻非参数估计
big data analysis
human resource flow region
estimation model simulation
K-nearest neighbor nonparametric estimation
