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分析及改进阻滞增长模型及对人口数量和结构的预测
引用本文:吴伯阳,吴瑞陶,王双宾,王俊力. 分析及改进阻滞增长模型及对人口数量和结构的预测[J]. 科技资讯, 2014, 12(25): 196-199
作者姓名:吴伯阳  吴瑞陶  王双宾  王俊力
作者单位:吉林大学数学学院 吉林长春 130012
基金项目:自然科学基金资助;项目号:J1310022.吉林大学数学学院国家人才基地本科生科研项目;J1030101.课题来源:吉林大学创新性实验项目
摘    要:目的改进阻滞增长模型及对深圳人口进行预测,为计划生育政策以及"单独二胎"政策提供有效的理论依据。方法通过建立阻滞增长模型,利用统计数据资料,求出了模型中的参数,并对1970—2010年的人口数量进行了预测。通过与实际人口数量进行比较,发现阻滞增长模型人对口数量的预测是较符合真实情况的。本文第二部分建立了Leslie模型。结果得到1990年人口11.433亿与真实值11.106亿十分接近,预测了2015—2030年人口数量的变化与人口年龄结构的变化,预测得出了2030年人口老龄化更加严重。结论发现Leslie模型不仅可以对人口总量进行准确预测,也可以反映人口变化的深层次因素。

关 键 词:人口  Leslie模型  预测  老龄化

Analysis and Improvement of Retarding Growth Model and the Prediction of Population Quantity and Structure
Wu Boyang,Wu Ruitao,Wang Shuangbin,Wang Junli. Analysis and Improvement of Retarding Growth Model and the Prediction of Population Quantity and Structure[J]. Science & Technology Information, 2014, 12(25): 196-199
Authors:Wu Boyang  Wu Ruitao  Wang Shuangbin  Wang Junli
Affiliation:Wu Boyang Wu Ruitao Wang Shuangbin Wang Junli (Jilin University, Institute of mathematics, Changchun, Jilin, 130012, China)
Abstract:Objective To improve block growth model and to forecast the population of Shenzhen,for the family planning policy and the"individual" open two--child policy to provide effective theory basis.Methods through the establishment of retarding growth model, the use of statistical data,calculate the parameters in the model,and population of 1970--2010 is forecasted.By comparing with the actual size of population,found that blocks the growth model to predict the number of people counterpart is more conform to reality. Result Leslie model is built up in the second part,the result is a population of 1.1433 billion, 1990 and 1.1106 billion is very close to the real value,forecasts the population change in 2015--2030 and the change of population age structure,forecasts the population aging is more serious in 2030.Conclusion Found Leslie model can not only to accurately predict the total population,also can reflect the deep factors of population change.
Keywords:Population  Leslie Model  Predict  Aging
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