Jie Yu
ABSTRACT
The evaluation of the short-term effects of the new "comprehensive two-child" policy will be analyzed in terms of the number of new born populations and the demographic structure. Through the regression analysis of the change trend before the implementation of the new policy, and comparing it with the current population, it is concluded that the implementation of the new policy will promote the growth of the new population. In the same way, compare the changing trends of the population proportions of each age group before and after the reform. The implementation of the new policy has played a certain role in increasing the number of new populations and adjusting the population structure. The analysis of population size and population structure requires prediction of various indicators. Population characteristics such as birth rate and death rate are constantly changing and developing. After the population reaches a certain size, its characteristics will stabilize over time. Therefore, the prediction of population structure (such as gender ratio, urban-rural ratio, age structure, etc.) Queue element method. Analyze the relationship between population size and population structure over time. And based on the predicted data and information, a qualitative analysis of economic development was made.
- Wang Zhengyan, Pan Yuanqing, Huangfu Guangyu, Li Tiange, Ge Liling. Overview of population forecasting methods in urban planning. Resource Development and Market, 2009, 25(03): 237-240.Google Scholar
- Shao Xiaofeng, Zhang Kexin. Research on the population growth model of Huanggang City. Mathematical Practice and Understanding, 2008(13): 97-101Google Scholar
- Jin Xin, Gao Lijuan, Jin Hui, Li Guizi. Based on the Malthus model for Gansu Province Population prediction.Journal of Qiqihar University (Natural Science Edition),2012,28(05):90-92.Google Scholar
- Wu Zhiyong, Huo Xiaoshu, Liu Jiashun. Numerical prediction of population in Tangshan City. Journal of Hebei University of Technology (Social Science Edition), 2010, 10(05): 19-21+25.Google Scholar
- Yan Huizhen. Application of logistic model in population prediction. Journal of Dalian Polytechnic University, 2008,27(4):333Google Scholar
- He Chun.The role of Malthusian population model in population prediction in Guangzhou.Journal of Guangdong University of Technology, 2010,27(3):31.Google Scholar
- Yang Lixia, Yang Guishan, Yuan Shaofeng. Application of Mathematical Model in Population Prediction——Taking Jiangsu Province as an Example Resources and Environment in the Yangtze River Basin, 2006,15(3):287.Google Scholar
- Statistical forecasting and decision-making. Shanghai University of Finance and Economics Press, Xu Guoxiang, 2012Google Scholar
- Tharwat, A., Mahdi, H., Elhoseny, M., Hassanien, A.E., Recognizing human activity in mobile crowdsensing environment using optimized k-NN algorithm, Expert Systems with Applications 107, pp. 32-44, 2018Google ScholarCross Ref
- Aging Population. Kelly Hensel. Food Technology. 2012Google Scholar
- Mu Guangzong. On the Reform of my country's Population and Fertility Policy. Journal of Central China Normal University: Humanities and Social Sciences Edition, 2014(01):37-45.Google Scholar
- Cai Fang. Theoretical Thinking on the Reform of the Management Mechanism of Population and Family Planning. China Population Science, 2001, 000(006):1-7.Google Scholar
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