INTELLIGENT COMPUTER NETWORK FOR RAILWAY TRANSPORT USING NEURAL NETWORK FOR DETERMINING THE OPTIMAL ROUTE

Authors

  • Victoria Pakhomova Ukrainian State University of Science and Technology: «Dnipro Institute of Infrastructure and Transport» https://orcid.org/0000-0002-0022-099X
  • Oleksandr Budnikov Ukrainian State University of Science and Technology: «Dnipro Institute of Infrastructure and Transport» https://orcid.org/0009-0007-4542-1617

DOI:

https://doi.org/10.30890/2567-5273.2025-40-02-038

Keywords:

information and telecommunications system, Ethernet family technologies, OSPF protocol, delay on routers, neural network tool, activation function, training algorithm, mean square error, epoch, accuracy

Abstract

At the present stage, the information and telecommunications system of railway transport uses local area networks of Ethernet family technologies and the OSPF protocol, when used in real time, a problem arises due to constant changes in the volume of tran

References

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Kolesnikov K.V., Karapetian A.R., & Bahan V.Y. (2016) Analiz rezultativ doslidzhennia realizatsii zadachi marshrutyzatsii na osnovi neironnykh merezh ta henetychnykh alhorytmiv. [Analysis of the research on the implementation of the routing problem based on neural networks and genetic algorithms]. Visnyk Cherkaskoho derzhavnoho tekhnolohichnoho universytetu. Seriia: Tekhnichni nauky, 1, 28-34 (in Ukraіnian).

Pakhomova V.M. (2018) Doslidzhennya informatsiyno-telekomunikatsiynoyi systemy zaliznychnoho transportu z vykorystannyam shtuchnoho intelektu: monohrafiya. [Research on the information and telecommunications system of railway transport using artificial intelligence: monograph]. Dnipro: Publishing House of PF «Standard – Service». 220 р. (in Ukraіnian).

Pakhomova V.M., & Оpriatnyi А.О. (2021) Prohramna model dlya vyznachennya optymal’nykh marshrutiv u kompyuterniy merezhi za dvokolonial’nym alhorytmom. [Software model for determining the optimal routes in a computer network based on the two-colonial ant algorithm]. Science and Transport Progress, 3(93), 38-49. DOI: 10.15802/stp2021/242046 (in Ukraіnian).

Pakhomova V.M., & Tsykalo I.D. (2025) Vyznachennya marshrutiv peredachi v merezhi informatsiyno-telekomunikatsiynoyi systemy zaliznychnoho transportu z vykorystannyam GWO. [Determination of transmission routes in the network of the information and telecommunication system of railway transport using GWO]. Visnyk of Kherson National Technical University: Helvetica Publishing House, 1(92)-2. 179-184. DOI: https://doi.org/10.35546/ (in Ukraіnian).

Pakhomova V.M., & Tsykalo I.D. (2018) Optimal route definition in the network based on the multilayer neural model. Science and Transport Progress, 6(78), 126-142. DOI: 10.15802/stp2018/154443 (in English).

Pakhomova V.M., & Mandybura Y.S. (2019) Optimal route definition in the railway information network using neural-fuzzy models. Science and Transport Progress, 5(83), 81-98. DOI: 10.15802/stp2019/184385 (in English).

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Published

2025-08-30

How to Cite

Пахомова, В., & Будніков, О. (2025). INTELLIGENT COMPUTER NETWORK FOR RAILWAY TRANSPORT USING NEURAL NETWORK FOR DETERMINING THE OPTIMAL ROUTE. Modern Engineering and Innovative Technologies, 2(40-02), 32–39. https://doi.org/10.30890/2567-5273.2025-40-02-038

Issue

No. 40-02 (2025)

Section

Articles

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