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| Titolo: | Comparative analysis of mathematical models and estimation of errors in computer modeling of the gas consumption process |
| Autori: | Shymchuk, Grigorii Lytvynenko, Iaroslav |
| Affiliation: | Ternopil Ivan Puluj National Technical University, Ukraine |
| Bibliographic description (Ukraine): | Shymchuk G. Comparative analysis of mathematical models and estimation of errors in computer modeling of the gas consumption process / Grigorii Shymchuk, Iaroslav Lytvynenko // Scientific Journal of TNTU. — Tern. : TNTU, 2026. — Vol 122. — No 2. — P. 107–119. |
| Bibliographic reference (2015): | Shymchuk G., Lytvynenko I. Comparative analysis of mathematical models and estimation of errors in computer modeling of the gas consumption process // Scientific Journal of TNTU, Ternopil. 2026. Vol 122. No 2. P. 107–119. |
| Bibliographic citation (APA): | Shymchuk, G., & Lytvynenko, I. (2026). Comparative analysis of mathematical models and estimation of errors in computer modeling of the gas consumption process. Scientific Journal of the Ternopil National Technical University, 122(2), 107-119. TNTU.. |
| Bibliographic citation (CHICAGO): | Shymchuk G., Lytvynenko I. (2026) Comparative analysis of mathematical models and estimation of errors in computer modeling of the gas consumption process. Scientific Journal of the Ternopil National Technical University (Tern.), vol. 122, no 2, pp. 107-119. |
| Is part of: | Вісник Тернопільського національного технічного університету, 2 (122), 2026 Scientific Journal of the Ternopil National Technical University, 2 (122), 2026 |
| Journal/Collection: | Вісник Тернопільського національного технічного університету |
| Issue: | 2 |
| Volume: | 122 |
| Data: | 26-mag-2026 |
| Submitted date: | 14-dic-2025 |
| Date of entry: | 13-ott-2026 |
| Editore: | ТНТУ TNTU |
| Place of the edition/event: | Тернопіль Ternopil |
| DOI: | https://doi.org/10.35784/ visnyk_tntu2026.02.107 |
| Parole chiave: | modeling mathematical model gas consumption cyclic random process ARIMA SARIMA cyclicity seasonality forecast |
| Number of pages: | 13 |
| Page range: | 107-119 |
| Start page: | 107 |
| End page: | 119 |
| Abstract: | The paper considers approaches to mathematical modeling of the gas consumption process based on three models: a model based on a cyclic random process and the classical ARIMA and SARIMA models. The gas consumption process is characterized by the presence of a trend, seasonality, cyclicity, and random disturbances, which necessitates the use of adequate mathematical models for its description and simulation. The paper presents a mathematical model of the gas consumption process in the form of an additive mixture of trend, cyclic, and random components. A comparative analysis of the ARIMA and SARIMA models, which are based on differencing operators and take seasonal features into account, is also provided. The models are compared in terms of adequacy, ability to capture cyclicity and seasonality, interpretability of parameters, and suitability for computer simulation and forecasting. To assess the accuracy of computer simulation of gas consumption process realizations, absolute and relative errors are used. It is shown that the SARIMA model is an effective baseline model for series with stable seasonality, whereas the model based on a cyclic random process is more suitable for describing gas consumption with a pronounced cyclic structure and is better suited for computer simulation tasks. |
| URI: | http://elartu.tntu.edu.ua/handle/lib/54162 |
| ISSN: | 2522-4433 |
| Copyright owner: | © Тернопільський національний технічний університет імені Івана Пулюя, 2026 |
| URL for reference material: | https://doi.org/10.33108/visnyk_tntu2021.04.087 https://elartu.tntu.edu.ua/bitstream/lib/36951/2/ICAAEIT_2021_Lupenko_S-Approach_to_gas_consumption_213-219.pdf https://ceur-ws.org/Vol-3468/short8.pdf https://ceur-ws.org/Vol-3039/paper23.pdf https://doi.org/10.1016/j.jngse.2021.103930 https://doi.org/10.1016/j.jpse.2025.100319 https://doi.org/10.3390/en14196021 https://doi.org/10.3390/en9090727 https://doi.org/10.1016/j.jngse.2020.103193 https://doi.org/10.1016/j.egyr.2023.09.051 https://doi.org/10.3390/technologies13100435 https://doi.org/10.3390/en14248597 https://doi.org/10.3390/en11082008 https://doi.org/10.3390/en14164905 https://doi.org/10.1016/j.eneco.2021.105760 https://doi.org/10.1016/j.energy.2022.125976 https://doi.org/10.1016/j.apenergy.2023.121503 https://doi.org/10.1016/j.eswa.2016.06.013 https://doi.org/10.1155/2021/5524479 https://doi.org/10.1016/j.engappai.2023.106005 https://doi.org/10.3390/en18143690 https://doi.org/10.1016/j.jclepro.2020.122096 https://doi.org/10.1080/15567249.2023.2274865 https://doi.org/10.7717/peerj-cs.1890 https://doi.org/10.1007/978-3-642-34913-3 |
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| Content type: | Article |
| È visualizzato nelle collezioni: | Вісник ТНТУ, 2026, № 2 (122) |
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