Neuronal network approach to study the operation of shuttle-service trains
https://doi.org/10.21780/2223-9731-2023-82-2-158-167
EDN: https://elibrary.ru/njglh
Abstract
Introduction. The authors study the section of the shuttle-service trains. Based on a detailed description and characterisation of the site, it is categorised as a man-machine and difficult-to-formalise system. It is not possible to study stability of such transport facilities using known criteria and methods. This study aimed at developing a new approach for assessing sustainability of a shuttle-service train system, taking account of its specific features and characteristics.
Materials and methods. The paper proposes the use of a neural network approach to assess the sustainability of shuttle-service trains. The input data used is a time series of freight flow on a section of the shuttle-service trains, which is the main operational indicator of the system under study. The method of artificial neural networks is chosen for modelling because it is a simple and effective tool for studying the system in question, with the values of the freight flow having a random character.
Results. An approach based on the power of neural networks is described. This indicator enables to assess quality of the model by reflecting the consistency of model results with actual data.
Discussion and conclusion. The approach presented may be used to assess the sustainability of a shuttle-service train system.
About the Authors
A. L. Kazakov
Irkutsk State University of Railway Transport; Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the RAS
Russian Federation
Russian Federation
Alexander L. Kazakov - Dr. Sci. (Phys. and Math.), Professor, Department of Operations Management, Irkutsk State University of Railway Transport; Chief Researcher, Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the RAS.
664074, Irkutsk, 15, Chernyshevskogo St.; 664033, Irkutsk, 134, Lermontov St.
Author ID: 14911
R. Yu. Upyr
Irkutsk State University of Railway Transport
Russian Federation
Russian Federation
Roman Yu. Upyr - Cand. Sci. (Eng.), Head of Department, Department of Operations Management, Irkutsk State University of Railway Transport.
664074, Irkutsk, 15, Chernyshevskogo St.
Author ID: 518343
A. D. Domojirova
Irkutsk State University of Railway Transport
Russian Federation
Russian Federation
Alena D. Domojirova - Postgraduate, Department of Operations Management, Irkutsk State University of Railway Transport.
664074, Irkutsk, 15, Chernyshevskogo St.
Author ID: 1039855
References
1. Aleksandrov A. E., Kovalev I. A. Design of automated control process for circular routes. Transport of the Urals. 2007;(1):41-47. (In Russ.). EDN: https://www.elibrary.ru/kdmkjz.
2. Malovetskaya E. V., Bolshakov R. S., Dimov A. V., Byshlyago A. A. Planning of qualitative indexes of railroad operational work in polygon technologies. In: IOP Conference Series: Materials Science and Engineering. Vol. 760: International Conference on Transport and Infrastructure of the Siberian Region (SibTrans-2019), 12—15 November 2019, Moscow, Russian Federation. [S. l.]: IOP Publ.; 2020. https://doi.org/10.1088/1757-899X/760/1/012041.
3. GOST 27.004-85. Reliability in technology. Technological systems. Terms and definitions. Introduction date 1986-07-01. Moscow: Standards Publishing House; 1986. 15 p. (In Russ.).
4. Domozhirova A. D., Upyr R. Yu. On the influence of delays in route trains on the recovery of train graphics. Modern Technologies. System Analysis. Modeling. 2021;(4):161-168. (In Russ.). https://doi.org/10.26731/1813-9108.2021.4(72).161-168.
5. Aleksandrov A. E., Timuhina E. N., Kovalev I. A. Optimization model of the transportation process with the use of unit trains. Transport of the Urals. 2017;(4):36-39. (In Russ.). https://doi.org/10.20291/1815-9400-2017-4-36-39.
6. Apattsev V. I., Sharov V. A. To realization of the Comprehensive program of phased transition to the organization of freight trains operation according to schedule on Russian railways. Science and Technology in Transport. 2011;(3):69-72. (In Russ.). EDN: https://www.elibrary.ru/oeyyhl.
7. Samarskiy A. A., Mikhaylov A. P. Mathematical modeling: ideas, methods. examples. Moscow: Fizmatlit; 2002. 320 p. (In Russ.). EDN: https://www.elibrary.ru/mvanqr.
8. Tokarev V. L. Integrated decision support systems for complex hard-to-formalizable tasks (for forecasting, control and diagnostics). Dr. Sci. (Eng.) thesis synopsis: 05.13.09. Tula; 2000. 48 p. (In Russ.).
9. Bychkov I. V., Kazakov A. L., Lempert A. A., Bukharov D. S., Stolbov A. B. An intelligent management system for the development of a regional transport logistics infrastructure. Automation and Remote Control. 2016;77(2):332-343. https://doi.org/10.1134/S0005117916020090.
10. Domozhirova A. D., Upyr R. Yu. Modeling of the stable conditions of the circular main tracker shuttle system. In: Railways: A Path to the Future: Proceedings of the I International Scientific Conference of Postgraduate and Young Scientists, 28—29April 2022, Moscow. Moscow: Railway Research Institute; 2022. p. 305-308. (In Russ.). EDN: https://www.elibrary.ru/iftmju.
11. Apattsev V. I., Podorozhkina A. V. On the estimation of technological stability of the freight terminal operation. Science and Technology in Transport. 2007;(1):8-13. (In Russ.). EDN: https://www.elibrary.ru/hznail.
12. Podorozhkina A. V. Integrated estimation procedure of technological stability of freight station. Science and Technology in Transport. 2010;(4):13-18. (In Russ.). EDN: https://www.elibrary.ru/mwlzbx.
13. Rybin P. K., Gorin R. V. Method of optimizing of the neural network structure for planning train arrival at pre-port stations. Vestnik transporta Povolzhya. 2017;(5):55-63. (In Russ.). EDN: https://www.elibrary.ru/yqzijy.
14. Afanas'ev V.N., Yuzbashev M.M. Time series analysis and forecasting. Moscow: Finansy i statistika; 2001. 228 p. (In Russ.). EDN: https://www.elibrary.ru/gdhzgx.
Review
For citations:
Kazakov A.L., Upyr R.Yu., Domojirova A.D. Neuronal network approach to study the operation of shuttle-service trains. RUSSIAN RAILWAY SCIENCE JOURNAL. 2023;82(2):158-167. (In Russ.) https://doi.org/10.21780/2223-9731-2023-82-2-158-167. EDN: https://elibrary.ru/njglh
Views:
327
.jpg)
Email this article 