Modeling and forecasting the parameters of a railroad transport system

Rebrin, O. I.; Zakharov, L. A.; Derksen, L. A.; Eremenko, V. I.

doi:10.1088/1742-6596/1679/3/032018

Please use this identifier to cite or link to this item: http://hdl.handle.net/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://hdl.handle.net/10995/102548
Access:	info:eu-repo/semantics/openAccess
SCOPUS ID:	85097537108
PURE ID:	20409752 a705607a-251b-4d29-94ed-a7ab2cd381df
ISSN:	17426588
DOI:	10.1088/1742-6596/1679/3/032018
metadata.dc.description.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, проиндексированные в SCOPUS и WoS CC

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