基于弱化算子的黑龙江省人口老龄化灰色预测  

Grey prediction of population aging based on weakening operator in Heilongjiang Province

作　　者：赵爽[1] 袁海燕[1] 郭霆 ZHAO Shuang;YUAN Haiyan;GUO Ting(College of Science,Heilongjiang Institute of Technology,Harbin 150050,China;College of Mechanical and Electrical Engineering,Heilongjiang Institute of Technology,Harbin 150050,China)

机构地区：[1]黑龙江工程学院理学院,哈尔滨150050 [2]黑龙江工程学院机电工程学院,哈尔滨150050

出　　处：《黑龙江工程学院学报》2024年第4期44-49,共6页Journal of Heilongjiang Institute of Technology

基　　金：黑龙江省自然科学基金项目(LH2023A019);黑龙江省属高校基本科研基金国基培育项目(2021GJ08);黑龙江工程学院博士科研启动基金项目(2022BJ05);黑龙江省博士后科研启动金项目(200323001)。

摘　　要：近年来,黑龙江省人口老龄化率高于全国,老龄人口规模持续上升,对医疗保障体系、劳动力资源结构以及养老服务体系等产生影响,因此,研究黑龙江省人口老龄化的预测问题具有十分重要的现实意义。针对黑龙江省人口老龄化的灰色特性,提出一种结合一阶弱化算子优化的均值GM(1,1)预测模型,对黑龙江省老龄人口发展趋势进行预报。以2006—2021年间的黑龙江省老龄人口原始数据为样本,构建基于一阶弱化算子均值GM(1,1)的黑龙江省人口老龄化预测模型,并与基于均值GM(1,1)的黑龙江省人口老龄化预测模型精度进行对比分析。结果表明:黑龙江省老龄人口的一阶弱化算子均值GM(1,1)预测模型精度高于传统的均值GM(1,1)模型,说明一阶弱化算子的均值GM(1,1)模型能够提高黑龙江省老龄人口预报精度。In recent years,the population aging rate of Heilongjiang Province is higher than that of the whole nation,and the size of the elderly population continues to rise,which has an impact on the medical security system,the structure of labor resources,and the elderly care service system,therefore,the study on the aging population prediction of Heilongjiang Province is of very important practical significance.Even GM(1,1)prediction model by first-order weakening operator optimization is proposed to predict the development trend of the elderly population of Heilongjiang Province,aiming at the grey characteristics of population aging in Heilongjiang Province.It is taken the aging population original data of Heilongjiang Province from 2006 to 2021 as samples,the population aging prediction model of Heilongjiang Province is established basing on even GM(1,1)model with first-order weakening operator,and then the accuracy of this above model is made a comparative analysis with the Heilongjiang population aging prediction model based on even GM(1,1).The results show that the accuracy of even GM(1,1)prediction model with first-order weakening operator is higher than the traditional even GM(1,1)prediction model in the aging population of Heilongjiang Province,which indicates that even GM(1,1)model with first-order weakening operator can improve accuracy in Heilongjiang elderly population prediction.

关 键 词：人口老龄化 一阶弱化算子 灰色预测 均值GM(1 1) 精度检验 

分 类 号：N941.5[自然科学总论—系统科学]