Application of mathematical methods to solving problems of digitization of population movement

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 char...

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Veröffentlicht in:ITM web of conferences Jg. 59; S. 2002
Hauptverfasser: Ketova, Karolina, Vavilova, Daiana
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: Les Ulis EDP Sciences 2024
Schlagworte:
Algorithms
Artificial intelligence
Big Data
Data processing
Data science
Demographics
Digital technology
Digitization
Forecasting
Human capital
Neural networks
Regression analysis
Statistical analysis
Statistical methods
ISSN:2271-2097, 2431-7578, 2271-2097
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Zusammenfassung: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.
Bibliographie:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20245902002