摘要
为了解决当前城市就业需求量预测过程存在的不足,设计基于云计算技术的城市就业需求量预测系统。首先,搭建城市就业需求量预测系统的云计算平台;然后,采集大量的城市就业需求量历史样本,将其划分为多个小的城市就业需求量历史样本集合,采用支持向量机对城市就业需求量历史样本进行建模,采用云计算平台的多个节点进行城市就业需求量预测;最后,对城市就业需求量预测结果进行融合,并与其他城市就业需求量预测系统进行对比实验。结果表明,云计算技术的城市就业需求量预测精度超过对比系统,而且提高了预测效率,具有十分明显的优越性。
In order to eliminate the deficiencies existing in the process of the current urban employment demand forecast,an urban employment demand forecasting system based on cloud computing technology is designed.The cloud computing platform of urban employment demand forecasting system is built first,and then a large number of historical samples of urban employment demand are collected and divided into several small historical sample sets.The support vector machine is used to model the historical samples of urban employment demand.The multiple nodes of cloud computing platform are used to predict the urban employment demand.The results of urban employment demand forecast are integrated and compared with those of other cities by experiments.The results show that the urban employment demand forecast system based on cloud computing technology is more accurate than the contrast system,and improves the forecasting efficiency,so it has obvious advantages.
作者
景毅
曹辉
JING Yi;CAO Hui(Southwest University of Science and Technology,Mianyang 621010,China)
出处
《现代电子技术》
2021年第1期122-126,共5页
Modern Electronics Technique
基金
四川省教育厅项目(CJSFZ19⁃22)。
关键词
城市就业
需求量预测
云计算技术
样本采集
样本建模
仿真实验
urban employment
demand forecast
cloud computing technology
sample acquisition
sample modeling
simulation experiment
