基于灰色聚类理论的人口年龄结构评估模型

Evaluation of Population Age Structure Model Using Grey Clustering Theory

由于经济发展水平与生育政策执行力度的差异,我国不同地区的人口年龄结构存在较大差异。以我国31个省市自治区为聚类对象,选取各阶段年龄的人口数量以及总抚养比等为聚类指标,定义了相应指标的白化权函数,给出了人口年龄结构评估的聚类模型,并且编写了相应的算法。利用这一模型把31个地区按年龄结构分成三类:优、中和差,然后对同一类的地区再次排序,进一步分析原因。文章的结果系统、客观、准确地评价出各地区年龄结构,对解决我国人口问题具有一定的参考价值。

Due to the differences in economic development level and fertility policy enforcement, the population age structures are quite diverse from different regions in China. 31 provinces and Autonomous regions are used as clustering objects, population from various age groups and total dependency ratio are chosen as clustering indexes and whitening weight functions from corresponding indexes are defined. Meanwhile, clustering models of the population age structure assessment are provided and corresponding algorithms are compiled. 31 regions are divided into 3 groups by the age structure： .excellent, normal, and poor. Then, sort again within each group to further analyze the reasons. The conclusion from our research provided a systematic, objective and accurate evaluation of age structure in various regiofis, it may has some reference value for solving China＇s population problems.