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JOURNALS // Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia // Archive

Dokl. RAN. Math. Inf. Proc. Upr., 2024 Volume 517, Pages 66–73 (Mi danma532)

MATHEMATICS

Graph condensation for large factor models

B. N. Chetverushkina, V. A. Sudakova, Yu. P. Titovb

a Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Moscow, Russia
b Moscow Aviation Institute (National Research University), Moscow, Russia

Abstract: An original method for processing large factor models based on graph condensation using machine learning models and artificial neural networks is developed. The proposed mathematical apparatus can be used to plan and manage complex organizational and technical systems, to optimize large socioeconomic objects of national scale, and to solve problems of preserving the health of the nation (searching for compatibility of medications and optimizing health care resources).

Keywords: factor model, graph condensation, clustering, eigenvector, eigenvalues.

UDC: 519.876

Received: 17.01.2024
Revised: 25.04.2024
Accepted: 29.06.2024

DOI: 10.31857/S2686954324030119


 English version:
Doklady Mathematics, 2024, 109:3, 246–251

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© Steklov Math. Inst. of RAS, 2024