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Title: Artificial Intelligence in Forecasting Demographic Processes
Author(s): Mezhov, Stepan
Krayushkin, Maxim
Granting Institution: Hochschule Anhalt
Issue Date: 2024
Language: English
Abstract: At the moment, there are no universal tools for forecasting indicators of socio-economic development in general and demographic in particular. However, the amount of budget allocations that are directed to solving personnel issues, creating social facilities and implementing other activities significant for economic, social and infrastructural development, development vectors depend on the forecast of demographic indicators by one-year-olds. In this article, a meaningful analysis is carried out an analysis of the researchers' work, based on the results of which it is determined that artificial intelligence models, in particular the most adaptive neural networks, are almost not used in predicting demographic indicators, forecasts based on models of artificial neural networks for all ages or by age groups, have almost no significance from the point of view of managing socio-economic development. The result of the research is a neural network methodological approach, methodology and tools for forecasting demographic processes for one-year-olds. The developed methodological approach to forecasting and tools are universal in the field of forecasting socio-economic indicators. In addition, the results described in the article can be used in other research in the field of forecasting, planning of any indicators.
Open Access: Open access publication
License: (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0(CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0
Appears in Collections:International Conference on Applied Innovations in IT (ICAIIT)

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