Enviar artigo por via de e-mail Graph Condensation for Large Factor Models
- Autores: Chetverushkin B.N.1, Sudakov V.A.1, Titov Y.P.2
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Afiliações:
- Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
- Moscow Aviation Institute (National Research University)
- Edição: Volume 517, Nº 1 (2024)
- Páginas: 66-73
- Seção: MATHEMATICS
- URL: https://jdigitaldiagnostics.com/2686-9543/article/view/647988
- DOI: https://doi.org/10.31857/S2686954324030119
- EDN: https://elibrary.ru/YAYMIS
- ID: 647988
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Resumo
The paper proposes an original method for processing large factor models based on graph condensation using machine learning models and artificial neural networks. The proposed mathematical apparatus can be used in problems of planning and managing complex organizational and technical systems, in optimizing large socio-economic objects on the scale of state sectors, to solve problems of preserving the health of the nation (searching for compatibility when taking medications, optimizing resource provision for healthcare).
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Sobre autores
B. Chetverushkin
Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Autor responsável pela correspondência
Email: office@keldysh.ru
Academician of the RAS
Rússia, MoscowV. Sudakov
Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Email: sudakov@ws-dss.com
Rússia, Moscow
Yu. Titov
Moscow Aviation Institute (National Research University)
Email: kalengul@mail.ru
Rússia, Moscow
Bibliografia
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- Нестеров В.А., Судаков В.А., Сыпало К.И., Титов Ю.П. Матрица нечетких корреспонденций модели авиационных перевозок // Известия Российской академии наук. Теория и системы управления. 2022. Т. 6. № 6. С. 95–102.
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