Analysis and Research on the Age Structure of Population Based on Multiple Regression Model

Yiwen Zhai, Jie Shen, Yun Wu, Tianhong Zhou

2023

Abstract

People’s desire to have children has not been strengthened under the three-child policy, and the most important thing is to look at the relevant supporting measures after childbearing. Based on the data of the population age structure of our country, this paper establishes a grey prediction model to predict the population status of China in the next 10 years after the opening of the three-child policy. At the same time, by using the index data of the main factors affecting the newborn population, a multiple regression model is established, and it is concluded that the three-child policy will indeed have an impact on the future population. The problem of population aging in China is still serious in the future, and the "double reduction" policy will have an impact on the new population.

Paper Citation

in Harvard Style

Zhai Y., Shen J., Wu Y. and Zhou T. (2023). Analysis and Research on the Age Structure of Population Based on Multiple Regression Model. In Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT; ISBN 978-989-758-677-4, SciTePress, pages 493-499. DOI: 10.5220/0012286500003807

in Bibtex Style

@conference{anit23,
author={Yiwen Zhai and Jie Shen and Yun Wu and Tianhong Zhou},
title={Analysis and Research on the Age Structure of Population Based on Multiple Regression Model},
booktitle={Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT},
year={2023},
pages={493-499},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012286500003807},
isbn={978-989-758-677-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT
TI - Analysis and Research on the Age Structure of Population Based on Multiple Regression Model
SN - 978-989-758-677-4
AU - Zhai Y.
AU - Shen J.
AU - Wu Y.
AU - Zhou T.
PY - 2023
SP - 493
EP - 499
DO - 10.5220/0012286500003807
PB - SciTePress