CAUSES OF DATA LOSS, TREATMENT AND PREVENTION METHODS

Kartashov A.; Oksyuta O.; Pavlov A.

doi:doi:10.58168/PPSPM2025_247-252

Home / Conferences / PROBLEMS AND PROSPECTS IN SYSTEMS AND PROCESS MODELING / PROBLEMS AND PROSPECTS IN SYSTEMS AND PROCESS MODELING : Materials of the All-Russian Scientific and Practical Conference, Voronezh, October 14, 2025

CAUSES OF DATA LOSS, TREATMENT AND PREVENTION METHODS

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CAUSES OF DATA LOSS, TREATMENT AND PREVENTION METHODS

Section: SECTION 2. COMPUTER-AIDED DESIGN SYSTEMS

Proceedings: PROBLEMS AND PROSPECTS IN SYSTEMS AND PROCESS MODELING : MATERIALS OF THE ALL-RUSSIAN SCIENTIFIC AND PRACTICAL CONFERENCE, VORONEZH, OCTOBER 14, 2025

UDC 004.9

Kartashov A. ¹

Oksyuta O. ²

Pavlov A. ³

Author and publication information

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

3. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

Type:

Сonference article

DOI:

https://doi.org/10.58168/PPSPM2025_247-252

Pages:

from 247 to 252

Published:

15.01.2026

Subject area:

UDC 004.9

Language:

Russian

Keywords:

mathematical models, forecasting, big data

Abstract and keywords

Abstract (English):
The work on creating effective forecasting and analytics models involves processing a large amount of information, called Big Data. For effective interaction with them, it is necessary to clearly define acceptable mathematical models that are correctly able to process such a volume of data and select the most appropriate one. Choosing the right model will allow you to further modify the program without additional difficulties.

Keywords:
mathematical models, forecasting, big data

References

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