基于GM(1,1)-SVM组合模型的中长期人口预测研究  

Medium and Long-term Population Prediction Based on GM(1,1)-SVM Combination Model

作　　者：徐翔燕[1] 侯瑞环 XU Xiang-yan;HOU Rui-huan(College of Information Engineering,Tarim University,Alar,XinJiang 843300,China)

机构地区：[1]塔里木大学信息工程学院,新疆阿拉尔843300

出　　处：《计算机科学》2020年第S01期485-487,493,共4页Computer Science

基　　金：塔里木大学校长基金青年创新资金项目(TDZKQN201824)。

摘　　要：准确预测未来人口数量,对制定相关经济政策具有现实意义。文中针对人口中长期预测影响因素较复杂、可用历史数据较少、单一模型局限性等特点,构建了灰色预测和支持向量机的组合预测模型。该模型将灰色预测模型和支持向量机模型进行组合,利用标准差法确定模型的权值信息,将模型应用于一师阿拉尔市人口的中长期预测,选取一师阿拉尔市1997-2017年的人口数据进行分析,对2018-2022年的数据进行预测。结果表明:与单一模型相比较,组合模型预测精度更高,相对误差低,且预测结果比较稳定,结果更符合实际。Accurate prediction of future population is of practical significance for the formulation of relevant economic policies.In this paper,a combined prediction model of grey and support vector machine is contructed according to the characteristics of complicated influencing factors of medium and long-term prediction,less available historical data,and the limitations of single model.The model combines the grey prediction model with the support vector machine model and uses the standard deviation method to determine the weight information.The model is applied to the medium and long-term prediction of the population of Alar City,and the population data of the first division of Alar City from 1997 to 2017 is selected for analysis,to predict the data 2018 to 2022.The result shows that,compared with the single model,the combined model has higher prediction accuracy and lower relative error,and the prediction result is relatively stable and more realistic.

关 键 词：灰色预测 支持向量机 组合模型 

分 类 号：C924[社会学—人口学]