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News
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Нейросетевая система прогнозирования результатов сезона итальянской футбольной лиги "Серия А"

Вестник Пермского университета. Серия: Математика. Механика. Информатика. 2023. № 1(60). С. 84–92.
Бутина Д., Yasnitsky L.

The article describes the development of neural network system for predicting the Italian football Lega Serie A season results. To select the initial set, thematic sites containing complete statistics on the necessary characteristics were used. The system based on cost characteristics has 12 input parameters. The average testing error of this system was 3 %. The system allows to evaluate the performance of a football team in a season within the ranking from 1 to 5 positions, where 1 is 1–4 places and entry into the Champions League, and 5 is the team leaving the league. The significance of the input parameters is revealed. The influence of input parameters on the result is also shown.

Research target: Computer Science Other social sciences
Language: Russian
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Keywords: forecastingнейронная сетьпрогнозfootballфутболsportСПОРТArtipcial neural network
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