2019
DOI: 10.1016/j.procs.2019.01.111
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Improvement of the technology of accelerated passage of low-capacity car traffic on the basis of scheduling of grouped trains of operational purpose

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Cited by 10 publications
(7 citation statements)
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“…Comparative analysis of regression methods to predict the time that it takes for a freight train to travel along a railroad section is given in Table 1. Table 1 Comparative analysis of regression methods to predict the time that it takes for a freight train to travel along a railroad section Based on the specified indicators (Table 1), the worst among the selected methods has proven to be a multiple linear regression model [22], which confirms the above conclusions regarding dependence (1), which describes complex non-linear processes of section operation. The most appropriate method was a regression model based on the artificial neural network, a multi-layer perceptron, MLP.…”
Section: Search For a Methods To Predict The Time That It Takes For A supporting
confidence: 56%
See 1 more Smart Citation
“…Comparative analysis of regression methods to predict the time that it takes for a freight train to travel along a railroad section is given in Table 1. Table 1 Comparative analysis of regression methods to predict the time that it takes for a freight train to travel along a railroad section Based on the specified indicators (Table 1), the worst among the selected methods has proven to be a multiple linear regression model [22], which confirms the above conclusions regarding dependence (1), which describes complex non-linear processes of section operation. The most appropriate method was a regression model based on the artificial neural network, a multi-layer perceptron, MLP.…”
Section: Search For a Methods To Predict The Time That It Takes For A supporting
confidence: 56%
“…The market of transport services increasingly faces the need for personalized mobility and logistics solutions that ensure lower risks in the transportation process. As practice shows, the technological process of cargo transportation by railroads has a lot of serious drawbacks, the main of which is the lack of predictability of the duration of operations execution in the process of transportation [1]. The high degree of uncertainty in the execution of a transportation process is particularly characteristic of the railroad system of Ukraine (AT "Ukrzaliznytsya"), which belongs to railroads with a system of trains traffic not complying with a departure schedule.…”
Section: Introductionmentioning
confidence: 99%
“…A discrete-event simulation (DES) will be the form of imitation modeling because the process of arrival of wagons to accumulation points, formation, dispatch and motion along the sections by transfer trains can be represented as a discrete-event one. This argument for railroad technological processes was substantiated in detail in papers [2,4,5].…”
Section: Theoretical Substantiation and Construction Of A Simulatimentioning
confidence: 88%
“…However, these models cannot be used to assess the effectiveness of functioning of marshalling parks where wagons are accumulated to the standard of a train. Adjusting the process of forming grouped trains to scheduled traffic, by using appropriate optimization models, makes it possible to accelerate the delivery of cargoes by railroad transport [5]; however, there is the unresolved issue on matching the dispatch of transfer trains at developed rail nodes with heavy passenger traffic.…”
Section: Literature Review and Problem Statementmentioning
confidence: 99%
“…Effective management of the transportation process is of great importance (Karnaukh et al, 2018;Rehman et al, 2016;Sandybayev, 2018) while ensuring the most rational use of the rolling stock and reducing the transportation costs and minimising environmental pollution. The rational organisation of any technological process at cargo delivery leads to reducing the delivery costs (Nel and Badenhorst-Weiss, 2012;Shramenko, 2015;Muzylyov et al, 2016;Prokhorchenko et al, 2019) as well as reaching the synergetic effect (Shramenko, 2016).…”
Section: Literature Reviewmentioning
confidence: 99%