Issue |
E3S Web Conf.
Volume 542, 2024
Green Horizon 2024: International Forum on Energy Management, Ecological Innovation, and Agro-Industrial Practices (YIFHG 2024)
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Article Number | 05007 | |
Number of page(s) | 8 | |
Section | Environmental Science Innovations | |
DOI | https://doi.org/10.1051/e3sconf/202454205007 | |
Published online | 27 June 2024 |
Statistical analysis of the impact of economic activity on the environment and the population in the regions of the Russian Federation
Financial University under the Government of the Russian Federation, 125993 Moscow, Russia
* Corresponding author: lrborisova@
Rosstat data on the dynamics of major socially significant diseases have been studied. The relationship between such diseases has been investigated. The influence of the main socially significant diseases and the main indicators of socio-economic development of the regions of the Russian Federation on the number of abortions has been studied. The most informative signs related to socially significant diseases and socio-economic development in all countries of the world have been selected. The influence of these signs on infant mortality has been studied. Machine learning methods collected in the Data Master Azforus (DMA) program were applied. The conducted research has demonstrated the effectiveness of using machine learning methods to identify patterns linking the frequency of socially significant diseases and indicators of socio-economic development.
© 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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