Issue |
ITM Web Conf.
Volume 59, 2024
II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
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Article Number | 02002 | |
Number of page(s) | 11 | |
Section | Interdisciplinary Mathematical Modeling and Applications | |
DOI | https://doi.org/10.1051/itmconf/20245902002 | |
Published online | 25 January 2024 |
Application of mathematical methods to solving problems of digitization of population movement
Kalashnikov Izhevsk State Technical University,
7, Studencheskaya street,
Izhevsk,
426069,
Russian Federation
* Corresponding author: vavilova_dd@mail.ru
This article is devoted to the development of algorithms and mathematical methods for digitalization of population movement. An algorithm for digitalization of demographic flows is proposed. It becomes possible at any time to obtain a complete description of both a specific person and a general characteristic of the state of the economic system in a given context (for example, age, gender, place of residence, type of settlement, level of education, level of health, level of culture). Within the framework of the problem, four tasks are identified, which the research is aimed at solving. The first task is constructing a scheme of a person's digital trace. The second task is aggregating digital traces and structuring demographic flows and related flows of human capital using Big Data technology. The next task is studying the characteristics, properties and qualities of the said flows using Data-analysis technology. The final task is analyzing and forecasting demographic and human capital flows using Data Science technology. When implementing Data Science technology, the use of mathematical methods of statistical data processing, methods of correlation and regression analysis, mathematical models, forecasting methods, artificial intelligence algorithms, including neural network models, is proposed to solve the task.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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