COMPARATIVE ANALYSIS OF MODERN TIME SERIES FORECASTING METHODS FOR SOLVING PRACTICAL PROBLEMS

Svitlana Sumets; Serhii Udovenko; Vadim Shergin; Larysa Chala; Svitlana Sumets; Serhii Udovenko; Vadim Shergin; Larysa Chala

doi:10.30888/2663-5712.2026-35-03-015

COMPARATIVE ANALYSIS OF MODERN TIME SERIES FORECASTING METHODS FOR SOLVING PRACTICAL PROBLEMS

Authors

Svitlana Sumets Kharkiv National University of Radio Electronics, Kharkiv https://orcid.org/0009-0005-4348-8848
Serhii Udovenko Simon Kuznets Kharkiv National University of Economics https://orcid.org/0000-0001-5945-8647
Vadim Shergin Kharkiv National University of Radio Electronics, Kharkiv https://orcid.org/0000-0002-4388-8180
Larysa Chala Kharkiv National University of Radio Electronics, Kharkiv https://orcid.org/0000-0002-9890-4790

DOI:

https://doi.org/10.30888/2663-5712.2026-35-03-015

Keywords:

machine learning, model, neural networks, forecasting, time series, ARIMA, ARIMAX, DEEPAR, PROPHET, SARIMA, SARIMAX

Abstract

The goal of this work is to develop a modified technology for error detection in text documents using a multilayer perceptron neural network. Each of the considered forecasting models has its own advantages and limitations when using them for the selected

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Published

2026-01-30

How to Cite

Сумець, С., Удовенко, С., Шергін, В., & Чала, Л. (2026). COMPARATIVE ANALYSIS OF MODERN TIME SERIES FORECASTING METHODS FOR SOLVING PRACTICAL PROBLEMS. SWorldJournal, 3(35-03), 34–47. https://doi.org/10.30888/2663-5712.2026-35-03-015