基于新陈代谢灰色模型对人口老龄化的预测  

Prediction of Population Aging Based on Metabolic Grey Model

作　　者：胥俊林 陈友军[1] XU Junlin;CHEN Youjun(Mathematics and Information School of China West Normal University,Nanchong Sichuan 637002,China)

机构地区：[1]西华师范大学数学与信息学院,四川南充637002

出　　处：《四川文理学院学报》2023年第2期47-53,共7页Sichuan University of Arts and Science Journal

基　　金：西华师范大学英才科研基金项目(17YC370);西华师范大学教学改革与研究重点项目(jgxmzd1824)。

摘　　要：近年来,我国老龄化人口数持续增长,人口老龄化已成为了在新时代所面临的最突出问题之一.以2005—2020年四川省老龄化人口数据为基础数据,充分考虑到扰动因素和驱动因素等新信息影响,以及模型中差分到微分直接过渡导致较大误差和建模数据的特点,构建改进的新陈代谢离散DGM(2,1)模型对四川省老龄化人口数进行预测.预测结果表明,四川省老年人口规模在未来的几年内不断扩大,将会面临巨大的养老压力.In recent years,China’s aging population has continued to grow.Population aging has become one of the most prominent problems in the new era.The paper is based on the aging population data of Sichuan Province from 2005 to 2020,and fully taking account of new information effects such as perturbation factors and drivers,as well as the characteristics of large errors caused by the direct transition from difference to differential in the model and modeling data,a modified metabolic discrete DGM(2,1)model is constructed to predict the trend of population aging in Sichuan province in the coming years.The prediction results show that the elderly population in Sichuan province will continue to expand in the next few years,and will face huge pension pressure.

关 键 词：DGM(2 1)模型 人口老龄化预测 新陈代谢 灰色预测 

分 类 号：N941.5[自然科学总论—系统科学] C924.24[社会学—人口学]