MODELING ARIMA AND LSTM TIME SERIES MODELS IN PYTHON

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DOI:

https://doi.org/10.30888/2709-2267.2025-30-00-002

Keywords:

time series analysis, machine learning, neural networks

Abstract

This article examines the theoretical foundations and practical aspects of applying ARIMA models, RNN architecture, and the working principles of LSTM, as well as their use for time series forecasting in Python using the Statsmodels and Keras libraries. C

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Published

2025-03-30

How to Cite

Doroshenko, I., & Tarasov, M. (2025). MODELING ARIMA AND LSTM TIME SERIES MODELS IN PYTHON. Sworld-Us Conference Proceedings, 1(usc30-00), 17–24. https://doi.org/10.30888/2709-2267.2025-30-00-002

Issue

No. usc30-00 (2025): Organization of scientific research in modern conditions '2025

Section

Abstracts

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Copyright (c) 2025 Authors

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This work is licensed under a Creative Commons Attribution 4.0 International License.