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我国部分省区人II增长预测典型案例分析
引用本文:赵宁,霍杰,王旭明. 我国部分省区人II增长预测典型案例分析[J]. 榆林高等专科学校学报, 2013, 0(6): 100-104
作者姓名:赵宁  霍杰  王旭明
作者单位:宁夏大学物理电气信息学院,宁夏银川750021
基金项目:国家自然科学基金项目(11265011);宁夏自然科学基金项目(NZ12161)
摘    要:人口与环境问题密切相关,在社会发展一定阶段以及有限的地理环境和生产力水平下,人口增长应保持在适当比例内。预测在一定的时期内一个地区的人口变化将有效地提高政府对人口一环境资源的宏观调控。Logistic模型是广被采用的人口预测模型,以宁夏回族自治区的人口变化为原始数据对Logistic模型进行参数修正,计算得到了人口与时间的关系,通过解析式得到了1989年到2011年宁夏回族自治区的总人口数,并得到了总人口数呈s型曲线增长,其预测值和《中国统计年鉴》中每一年所对应的总人口数基本上一致,相对误差小于5%。利用同样的方法对中国其他五个省份总人口数进行预测,并进行了比较,分析影响人口变化的因素,对人口一资源的宏观调控有重要的指导意义。

关 键 词:Logistic模型  人口预测  老龄化

Case Studies on Population Forecast of Some Typical Regions in China
Affiliation:ZHAO Ning, HUO Jie, WANG Xu - ming (School of Physics and Electrical Information ,Ningxia University ,Yinchuan 750021 ,Ningxia)
Abstract:Population is closely related to environmental issues. Population proliferation should be maintained at an appropriate proportion under a certain stage of social development and limited geographical environment and produc tivity. Predicting population changes of a region over a certain period of time will effectively improve the government macro control of population - environmental resources. Logistic model is widely used in population projection model. In this paper, we put out a relation formula about population and time through numerical calculations of Lo gistic Model, and the Ningxia Hui Autonomous Region's population changes are used as the original data. Using the formula, we get the total population of Ningxia Hui Autonomous Region between 1989 to 2011, and the total population growth shows S - shaped curve. The predictive values of total population for each year are consistent with China Statistical Yearbook, and the relative error is less than 5%. Then we predict and compare the total popula tion of the other five tion changes, it will sources. pro be vinces in China with the same method. By the analysis of the factors which affects popula a important guiding significance for macro - control of population - environmental resources
Keywords:Logistic model  population prediction  aging
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