Graph Condensation for Large Factor Models

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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Publication Details

Journal
Доклады Российской академии наук Математика информатика процессы управления
Published
2024-10-03
DOI
https://doi.org/10.31857/s2686954324030119
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Graph Condensation for Large Factor Models

Vladimir Anatolievich Sudakov, Yu. P. Titov, Б. Н. Четверушкин
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Доклады Российской академии наук Математика информатика процессы управления
Complex Network Analysis Techniques
article

Graph Condensation for Large Factor Models

Vladimir Anatolievich Sudakov, Yu. P. Titov, Б. Н. Четверушкин
article en

Abstract

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).

Доклады Российской академии наук Математика информатика процессы управленияVol. 517(1)
Moscow Aviation Institute (RU), Keldysh Institute of Applied Mathematics (RU)
Openalex Percentile: Top 84%
Complex Network Analysis Techniques
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