毕 业 论 文（设
计）
题 目 基于神经网络的中国人口预测算法研究
所在院(系) 数学与计算机科学学院
专业班级 信息与计算科学1102班
指导教师 赵 晖
完成地点 陕西理工学院
2015年 5 月25日
基于神经网络的中国人口预测算法研究
作 者：宋 波
（陕理工学院数学与计算机科学学院信息与计算科学专业1102班，陕西 汉中
723000）
指导教师：赵 晖
[摘要]我国现正处于全面建成小康社会时期,人口发展面临着巨大的挑战,经济社会发展与资源环境的矛盾日益尖锐。我国是个人口大国、资源小国，这对矛盾将长期制约我国经济社会的发展。准确地预测未来人口的发展趋势，制定合理的人口规划和人口布局方案具有重大的理论意义和实用意义。本文介绍了人口预测的概念及发展规律等。
首先，本文考虑到人口预测具有大量冗余、流动范围和数量扩大的特性，又为提高人口预测的效果，因此，使用归一化对人口数据进行了处理，该方法不需要离散化原数据，这样就保证了人口预测的准确性和原始数据的信息完整性。其次，本文提出了一种基于神经网络预测的优化算法，该算法避免了人们在预测中参数选择的主观性而带来的精度的风险，增强了人口预测的准确性。同时，为说明该算法的有效性，又设计了几种人们通常所用的人口模型和灰色预测模型算法，并用相同的数据进行实验，得到了良好的效果，即本文算法的人口预测最为准确，其预测性能明显优于其他算法，而这主要是参数的选择对于增强预测性方面的影响，最终导致人口预测精确度。同时，在算法的稳定性和扩展性方面，该算法也明显优于其他算法。
考虑出生率、死亡率、人口增长率等因素的影响，重建神经网络模型预测人口数量。
[关键词] 神经网络人口模型灰色预测模型软件
Population projections based on neural networks
Author: Song Bo
(Grade11,Class 2, Major in Information and computing science, Mathematics and
computer science Dept.
Tutor:Zhao Hui
Abstract：Our country is now in the period of building a moderately prosperous society,
demographic development is faced with great challenges, the contradiction between economic and
social development and environmental protection increasingly sharp. Our country is populous
country, resources small country, this contradiction will have long hindered the development of
economy and society. Accurately predict the future demographic trends, population planning and
development of rational population distribution program has great theoretical and practical
significance. This paper introduces the concept of population projections and development law and
so on.
Firstly, taking into account the population predicted to have a lot of redundancy, to expand the
scope and volume of flow characteristics, but also to improve the population projections of the effect,
therefore, the use of normalized data were processed on the population, which does not require
discrete raw data, this ensures that the population forecast accuracy and completeness of
information the original data. Secondly, this paper presents an optimization algorithm based on
neural network prediction, the algorithm avoids the people in the forecast parameters and risks
subjectivity accuracy, and enhance the accuracy of population projections. Meanwhile, in order to
show the effectiveness of the algorithm, and designed several people population model is usually
used and the gray prediction model and algorithm, and tested using the same data, obtained good
results, that population is the most accurate prediction algorithm, which forecast outperforms other
algorithms, which mainly affect the selection parameters for enhanced predictability, eventually
leading to population forecasting accuracy. Meanwhile, in the stability and scalability algorithm, the
algorithm is also significantly better than the other algorithms.
Consider the impact of fertility, mortality, population growth and other factors, rebuild the
neural network model to predict population.
Key words:Neural network population model grey prediction model software
目录
1. 绪论 ..................................................1.1 引言 ..................................................
1.2 研究的背景及意义 ......................................
1.2.1研究背景 ..........................................
1.2.2研究意义 ..........................................
1.3 人口预测发展及研究现状 ................................
1.4 基本目标及主要内容 ....................................
1.5 组织结构 ..............................................
2.三种模型基本概念和原理 ..................................2.1阻滞增长模型（模型） ...................................
2.2灰色系统预测模型 .......................................
2.2.1 研究领域及理论 ...................................
2.2.2灰色模型发展 ......................................
2.3 神经网络预测模型研究概述 ............................. 12.3.1神经网络模型概念 ................................. 12.3.2研究的发展 ....................................... 12.3.3研究领域 ......................................... 12.3.4神经网络学习过程 ................................. 13.本文算法描述 .......................................... 13.1阻滞增长模型的算法： .................................. 13.2算法 ................................................. 13.3神经网络算法实验 ...................................... 14.数据处理 .............................................. 14.1模型预测 ............................................. 14.2模型的求解 ............................................ 24.3 BP神经网络人口预测模型 ............................... 25.仿真实验及分析 ........................................ 25.1 数据来源说明 ......................................... 25.2 实验步骤 ............................................. 25.3 实验结论及分析 ....................................... 25.4 实验结论 ............................................. 2致谢 .................................................... 3
