基于灰色预测模型的老龄人口预测

发布时间：2018-06-24 20:47

本文选题：老龄人口 + 灰色预测　；参考：《哈尔滨工业大学》2017年硕士论文

【摘要】：我国人口老龄化问题正在日益严重,由于人口结构的老化,各种社会问题开始显现;由于老龄人口的比例的持续增加,使得青壮年劳动力的比例持续下降,对国家和社会的发展产生了影响。更重要的是,我国目前面临的是“未富先老”的不利局面。老龄人口增加的同时,并没有完善和足够的政策体系来支持,使得家庭负担和社会负担持续加重。于是,对老龄人口的精确预测的重要性凸显。如今对于人口预测的方法可谓多种多样,各种方法都有各自的优势和不足。本文将研究灰色预测模型,并利用该模型和优化后的该模型对老龄人口进行预测,具体研究分为三个部分:第一,本文将首先介绍灰色模型的相关理论,并给出原始的灰色预测模型,同时给出预测的步骤。并且本文将给出几种预测精度的检验方法。对模型精度进行检验并提出优化方向。第二,根据对原始模型的研究,本文将从几个方向对模型提出优化。就序列光滑性给出函数变换提高光滑性的改进;就模型背景值方向给出背景值参数化改进;也给出利用灰色组合预测模型提高预测精度的方法。第三,本文将就2005年至2014年的老龄人口数进行模型的模拟。分别将数据用原始模型及改进后的模型进行测试,比较各个模型的模拟精度。选择精度最高的优化方式给出后续十年老龄人口的预测值。
[Abstract]:The problem of aging population in our country is becoming more and more serious. Due to the aging of the population structure, various social problems are beginning to appear. As the proportion of the aged population continues to increase, the proportion of the young and middle-aged labor force continues to decline. It has had an impact on the development of the country and society. More importantly, China is now facing the disadvantage of being old before becoming rich. While the aging population increases, there is no perfect and sufficient policy system to support the family burden and social burden. Therefore, the importance of accurate prediction of the elderly population is highlighted. Nowadays, there are a variety of methods for population forecasting, and each method has its own advantages and disadvantages. This paper will study the grey prediction model, and use this model and the optimized model to predict the aging population. The specific research is divided into three parts: first, this paper will first introduce the relevant theories of the grey model. The original grey prediction model is given, and the steps of prediction are also given. And this paper will give several methods to test the prediction accuracy. The accuracy of the model is tested and the optimization direction is proposed. Secondly, according to the study of the original model, this paper will optimize the model from several directions. The improvement of function transformation to improve smoothness, the parameterization of background value to the direction of background value of the model, and the method of improving prediction accuracy by using grey combination forecasting model are given. Thirdly, this paper will simulate the aging population from 2005 to 2014. The data were tested with the original model and the improved model, and the simulation accuracy of each model was compared. Select the most accurate optimization method to give the prediction value of the aging population for the next ten years.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：C924.24;N941.5

【参考文献】