Please use this identifier to cite or link to this item:
https://elar.urfu.ru/handle/10995/102548
Title: | Modeling and forecasting the parameters of a railroad transport system |
Authors: | Rebrin, O. I. Zakharov, L. A. Derksen, L. A. Eremenko, V. I. |
Issue Date: | 2020 |
Publisher: | IOP Publishing Ltd |
Citation: | Modeling and forecasting the parameters of a railroad transport system / O. I. Rebrin, L. A. Zakharov, L. A. Derksen, et al. — DOI 10.1088/1742-6596/1679/3/032018 // Journal of Physics: Conference Series. — 2020. — Vol. 1679. — Iss. 3. — 032018. |
Abstract: | The article describes an algorithm for constructing a mathematical model to predict the demand for railway passenger transportation. The model based on the SARIMAX methodology, considering the influence of seasonality and external variables on demand. The average absolute error of prediction result of the created model with the calculated parameters is 8%. The created model can be used as a decision support system in the field of passenger transportation. © Published under licence by IOP Publishing Ltd. |
Keywords: | DECISION SUPPORT SYSTEMS RAILROADS AVERAGE ABSOLUTE ERROR MODEL-BASED OPC MODELING AND FORECASTING ON DEMANDS PASSENGER TRANSPORTATION RAILWAY PASSENGERS SEASONALITY TRANSPORT SYSTEMS FORECASTING |
URI: | http://elar.urfu.ru/handle/10995/102548 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 85097537108 |
WOS ID: | 000773388000119 |
PURE ID: | a705607a-251b-4d29-94ed-a7ab2cd381df 20409752 |
ISSN: | 17426588 |
DOI: | 10.1088/1742-6596/1679/3/032018 |
Sponsorship: | The article was prepared with the financial support of the Center of Competence «Systems Engineering» established within the International Scientific and Methodological Center for the Transfer of Competencies of the Digital Economy of Ural Federal University, created in accordance with the Agreement dated 09.12.2019 No. 075-15-2019-1907. |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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2-s2.0-85097537108.pdf | 725,9 kB | Adobe PDF | View/Open |
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