人口预测的改进Leslie模型

Jinjing Ma, Yongkang Peng, Lianyu Wu
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引用次数: 0

摘要

莱斯利模型以1953 - 2020年中国人口数据为基础,结合各地区各年龄段育龄妇女生育率、出生人口性别比、死亡率、各年龄段城乡人口迁移率、曲线拟合迁移函数,并应用ARIMA预测死亡率,构建离散人口动态系统,预测中国未来人口发展轨迹。比较了改进的Leslie、Leslie、BP和Malthus模型的错误率。改进的Leslie模型比其他模型更稳定,平均错误率为0.09%,具有良好的模型泛化能力。结果表明,改进后的Leslie模型预测,在国家调控政策下,人口总量将缓慢增长,并在2045年左右达到峰值,然后下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Improved Leslie Model for population Forecasting
Based on China’s population data from 1953 to 2020, the Leslie model combines the fertility rate of women of childbearing age by region and age, the sex ratio of the birth population, the mortality rate, the migration rate between urban and rural areas by age, the curve fitting migration function, and the application of ARIMA to predict mortality rates to construct a discrete population dynamics system in order to predict China’s future population development trajectory. The improved Leslie, Leslie, BP and Malthus models were compared in terms of error rates. The improved Leslie model was more stable than the rest of the models and had an average error rate of 0.09%, with good model generalization ability. The results show that the improved Leslie model predicts that the total population will slowly increase under the national regulation policy, and will reach a peak by around 2045 and then decline.
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