基于组合预测模型的国内人口老龄化预测分析

Linlin Su, Yaxin Zhou, Qi Fang
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引用次数: 1

摘要

:弄清人口老龄化的影响因素,对有效应对老龄化挑战,促进中国经济社会发展具有现实意义。本文以人口老龄化影响因素为研究对象,在合理假设的基础上,构造了二次指数平滑预测、修正灰色预测和BP神经网络预测三种单一模型,并分别推导了样本内预测的误差平方和。然后根据误差平方和逆法确定权重,构建了人口老龄化的联合预测模型,得出了无论样本内预测还是样本外预测,联合预测模型的预测都更有效的结论;然后利用该模型进行预测,预测结果表明,未来中国人口老龄化问题仍将日益严重。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Domestic Population Aging Forecast Based on Combined Forecast Model
: It is of practical significance to clarify the influencing factors of population aging to effectively respond to the challenges of aging and promote the development of China's economy and society. This paper takes population aging influencing factors as the research object, and on the basis of reasonable assumptions The three single models of quadratic exponential smoothing prediction, modified gray prediction and BP neural network prediction are constructed, and then the error sum of squares of in-sample prediction is derived separately, and then the weights are determined according to the inverse of the error sum of squares method to construct a combined prediction model of population aging, and the conclusion that the prediction of combined prediction model is more effective regardless of in-sample prediction or out-of-sample prediction is drawn; and then the model is used to predict the prediction results show that the problem of population aging in China will remain increasingly serious in the future.
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