Algorithm for calculating the forecasted passenger flow of innovative railway transport based on a neural model
- 作者: Zhuravleva N.A.1, Batalova N.V.1
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隶属关系:
- Emperor Alexander I Petersburg State Transport University
- 期: 卷 11, 编号 3 (2025)
- 页面: 474-485
- 栏目: Original studies
- URL: https://ogarev-online.ru/transj/article/view/328157
- DOI: https://doi.org/10.17816/transsyst688684
- ID: 328157
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全文:
详细
Aim: to create a neural network toolkit for predicting passenger traffic by innovative (high-speed) rail transport.
Materials and methods: statistical data on passenger traffic on all modes of transport in the areas of high-speed railway lines. Methods: econometric modeling, multilayer perceptron.
Results: an algorithm for planning passenger traffic on high-speed railway lines based on an intelligent neural model.
Conclusion: The ability of the neural network model to "learn" allows to increase the reliability of population mobility forecasts when evaluating HSRT projects.
作者简介
N. Zhuravleva
Emperor Alexander I Petersburg State Transport University
编辑信件的主要联系方式.
Email: zhuravleva_na@mail.ru
ORCID iD: 0000-0003-3566-9225
SPIN 代码: 8599-5636
Scopus 作者 ID: 56583893700
Dr Sci. (Economics), Professor
俄罗斯联邦, St. PetersburgN. Batalova
Emperor Alexander I Petersburg State Transport University
Email: natalyabatalova@yandex.ru
ORCID iD: 0000-0002-5948-7226
SPIN 代码: 4027-4771
Senior Lecturer
俄罗斯联邦, St. Petersburg参考
- Zaitsev AA, Talashkin GN. Economics of High-Speed Infrastructure. Bulletin of scientific research results. 2013;4(9):69–75. EDN: SERDED (In Russ.)
- Tsidenov AS. The creation of high-speed highways is the key to the country's success in the present and future. Transport Rossiiskoi Federatsii. Zhurnal o nauke, praktike, ekonomike. 2016;5(66):10–15. EDN: WZJSSH
- Mironova IA, Tishchenko TI, Frolova MP. Problems of assessing the socio-economic efficiency of a large-scale infrastructure project using the example of a high-speed highway. Rossiiskii ekonomicheskii zhurnal. 2022;3. (In Russ.) doi: 10.33983/0130-9757-2022-3-100-119
- Zhuravleva NA. Economic assessment of intermodal effects of high-speed transport systems in the economy of the new technological order.
- Bulletin of scientific research results, 2018; 4:31-40. EDN: YYSESD (In Russ.)
- Vasilyeva ME, Volkova EM, Romanov AS. Intelligent transport systems in Russian megacities: the essence, structure and directions of development. Modern Transportation Systems and Technologies. 2023;9(4):117–128. doi: 10.17816/transsyst202394117-128 (In Russ.)
- Rosstat – Natsionalnie scheta [internet] Accessed: Jul 14, 2025 Available from: https://rosstat.gov.ru/statistics/accounts Accessed: Jul 14, 2025
- Dannie Komiteta po razvitiyu turizma Sankt‑Peterburga. Otchet o khode realizatsii Gosudarstvennoi programmi Sankt-Peterburga «Razvitie sferi turizma v Sankt-Peterburge» za 2019 god i za I polugodie 2020 goda. [internet] Accessed: Jul 14, 2025Available from: https://www.gov.spb.ru/gov/otrasl/c_tourism/otchet-na-pravitelstvo-o-hode-realizacii-gosudarstvennoj-programmy-san/ (In Russ.)
- Dannie Komiteta po razvitiyu turizma Sankt‑Peterburga. Statistika razvitiya turisticheskogo rinka. "Turbarometr Sankt‑Peterburga 2023". Analiticheskie pokazateli turizma i industrii gostepriimstva Sankt‑Peterburga v 2023 g. [internet] Accessed: Jul 14, 2025 Available from: https://businesstat.ru/russia/services/hotels_and_tourism/tourism/?yclid=12898454363016527871 (In Russ.)
- Tolstikh VN. Pertseptron, neironnaya set. Chto dalshe? Paradigma, 2022;37. (In Russ.) EDN: WLFBPI
- Zou W, Chen L, Xiong J. High-speed railway, market access and economic growth. International Review of Economics & Finance. 2019. doi: 76. 10.1016/j.iref.2019.11.014.
- Cascetta E, Cartenì A, Henke I, Pagliara F. Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives. Transp Res Part A Policy Pract. 2020;139:412–428. doi: 10.1016/j.tra.2020.07.008
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