DATA PREPARATION AND SELECTION OF A FORECASTING METHOD

Kartashov A.; Oksyuta O.; Kushcheva I.

doi:doi:10.58168/PPSPM2025_261-267

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DATA PREPARATION AND SELECTION OF A FORECASTING METHOD

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DATA PREPARATION AND SELECTION OF A FORECASTING METHOD

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

Kushcheva I. 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_261-267

Pages:

from 261 to 267

Published:

15.01.2026

Subject area:

UDC 004.9

Language:

Russian

Keywords:

data analysis, forecasting, data, regression analysis, Bayesian models

Abstract and keywords

Abstract (English):
The use of forecasting methods allows companies and individuals responsible for choosing development strategies to adapt to changes before they occur. The ability to anticipate changes and predict future directions enables businesses to take clear and decisive actions. Therefore, it is crucial to understand the different forecasting methods available and how they work.

Keywords:
data analysis, forecasting, data, regression analysis, Bayesian models

References

1. Savochkina, D. S. Issledovanie tehnologiy vizualizacii informacii i dannyh i razrabotka prototipa modulya vizualizacii mnogomernyh dannyh v sistemah analitiki / D. S. Savochkina // Mezhdunarodnaya nauchno-prakticheskaya konferenciya po komp'yuternoy i informacionnoy bezopasnosti (INFSEC 2023): sbornik statey, Ekaterinburg, 30 iyunya 2023 goda / OOO «Institut cifrovoy ekonomiki i prava». – Ekaterinburg: Obschestvo s ogranichennoy otvetstvennost'yu "Institut Cifrovoy Ekonomiki i Prava", 2023. – S. 108-109.

2. Dudorova, A. V. Primenenie Bootstrap metoda v analize povedencheskih dannyh i metod vizualizacii dannyh vybora iz treh ob'ektov / A. V. Dudorova, D. A. Podgrudkov, E. P. Kruchenkova // Zoologicheskiy zhurnal. – 2023. – T. 102, № 3. – S. 349-353. – DOIhttps://doi.org/10.31857/S0044513423020046. EDN: https://elibrary.ru/HPGOQP

3. Aksenov, M. S. Kratkie svedeniya o power Bi: zagruzka dannyh, vizualizaciya dannyh / M. S. Aksenov, R. E. Soldatov // Pedagogicheskoe obrazovanie na Altae. – 2017. – № 2. – S. 7-13. EDN: https://elibrary.ru/ZXKVWD

4. Gamayunova, O. A. Analiz dannyh i BI-sistemy v marketinge: vizualizaciya i interpretaciya dannyh dlya prinyatiya resheniy / O. A. Gamayunova // Dostizheniya nauki i tehnologiy-DNiT-11-2023 : Sbornik nauchnyh statey po materialam II Vserossiyskoy nauchnoy konferencii, Krasnoyarsk, 27–28 fevralya 2023 goda. Tom Vypusk 7. – Krasnoyarsk: Obschestvennoe uchrezhdenie "Krasnoyarskiy kraevoy Dom nauki i tehniki Rossiyskogo soyuza nauchnyh i inzhenernyh obschestvennyh ob'edineniy", 2023. – S. 364-368.

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