首页|"七普"视角下江西省人口结构转变及发展趋势研究

"七普"视角下江西省人口结构转变及发展趋势研究

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以江西省1994-2021年统计年鉴数据为基础,分别从人口自然结构、社会结构、地域结构3个方面对江西省人口结构特征及其变化进行研究,并通过BP神经网络模型和GM灰色模型进行人口结构预测,进而利用熵权法对人口结构发展进行评价.结果显示:全省人口自然增长放缓,年龄结构高龄化,人口结构中存在低生育率、低死亡率的现象;老少抚养比分异减小,人口抚养比趋于上升,人口性别比趋于平衡但仍处于失衡状态;城镇化率增速减缓,人口空间分布存在显著差异;预测结果显示江西省人口将进入放缓增长阶段.采用熵权法评价人口结构后可见,人均教育财政支出、人均国民生产总值、出生率、人口自然增长率对人口结构的优化和人口高质量发展起着重要作用.
Research on the Characteristics and Development Trend of Population Structure in Jiangxi Province from the 7th National Population Census
Based on the statistical yearbook data of Jiangxi Province from 1994 to 2021,this paper studies the characteristics and changes of population structure in Jiangxi Province from three aspects:natural structure,social structure and geographical structure,predicts the population structure by BP neural network model and GM gray model,and evaluates the development of population structure by entropy weight method.The results show that:the natural population growth in the province is slo-wing down,the age structure is aging,and there is a phenomenon of low fertility and low mortality in the population structure;the difference between the old and young dependency ratio decreases,the population dependency ratio tends to rise,the population sex ratio tends to balance but is still in an imbalance;the growth rate of urbanization rate slows down,and there are significant differences in the spatial distribution of population;the prediction results of BP neural network model and GM gray model show that the population of Jiangxi Province will enter a slow growth stage.After using the en-tropy weight method to evaluate the population structure,it can be seen that per capita financial ex-penditure on education,per capita GNP,birth rate,and natural population growth rate play an im-portant role in the optimization of the population structure.

population structureBP neural networkgray forecastpopulation forecasting

管小春、乌敦、王婉婷

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内蒙古师范大学地理科学学院,010022,呼和浩特

人口结构 BP神经网络 GM灰色模型 人口预测

2023

江西科学
江西省科学院

江西科学

影响因子:0.286
ISSN:1001-3679
年,卷(期):2023.41(1)
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