The Application of Markov Chains in Population Migration Research
- DOI
- 10.2991/978-2-38476-475-4_91How to use a DOI?
- Keywords
- Population mobility; Markov chain matrix; Population growth
- Abstract
Urban and rural population mobility is an important part of population movement. Linear algebra and its related application models are the main tools for studying the migration and changes of urban and rural populations. The purpose of this paper is to use Markov chain matrices to study the trend of urban and rural population migration, analyze the changes of urban and rural populations between different years, and thereby predict the future trend of urban and rural population migration. This article will introduce the definition of urban and rural population migration, calculate the changes and migration trends of urban and rural populations over 10 years, 30 years and 50 years using the correlation matrix model, support it with data and images, and conduct comprehensive analysis to make long-term predictions. In addition, this article also considers the impact on the proportion of urban and rural populations in the short and long term by adding a new influencing factor, that is, from the perspectives of urban population growth rate and rural population growth rate.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Sitong Shen AU - Yiyang He PY - 2025 DA - 2025/11/11 TI - The Application of Markov Chains in Population Migration Research BT - Proceedings of the 2025 10th International Conference on Modern Management, Education and Social Sciences (MMET 2025) PB - Atlantis Press SP - 817 EP - 826 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-475-4_91 DO - 10.2991/978-2-38476-475-4_91 ID - Shen2025 ER -