Analysis of visual models of big data technology for transportation process monitoring based on freight railcar storage

Авторы: 
A. I. Vlasov
Podorin Aleksandr A.
Artur Yu. Malevannyi
Dmitrii V. Rubtsov
Дата поступления: 
15.09.2020
Библиографическое описание статьи: 

Vlasov A. I., Podorin A. A., Malevanniy A. Yu., Rubtsov D. V. Analiz vizual'nykh modeley tekhnologii bol'shikh dannykh pri monitoringe perevozochnogo protsessa na osnove khranilishcha reysov gruzovykh vagonov [Analysis of visual models of big data technology for transportation process monitoring based on freight railcar storage]. Sovremennye tekhnologii. Sistemnyi analiz. Modelirovanie [Modern Technologies. System Analysis. Modeling], 2020, No. 3(67), pp. 100–108. 10.26731/1813-9108.2020.3(67).100-108

Рубрика: 
Transport
Год: 
2020
Номер журнала (Том): 
№3(67)
УДК: 
656.213
DOI: 

10.26731/1813-9108.2020.3(67).100-108

Файл статьи: 
Иконка PDF 100-108.pdf
Страницы: 
100
108
Аннотация: 

This article analyzes how to evaluate the efficiency of the transportation process. It is mainly focused on methods and means of monitoring its basic indicators. When considering data structures for storing information on railcars and their journeys, it was revealed that in the framework of modern realities existing monitoring methods are not effective enough, since large-scale data processing is required. After an analysis of the existing structure, it was found that the initial data structure includes a set of disparate data, which creates difficulties and inaccuracies in monitoring the transportation process. Therefore, its restructuring is proposed. The new structure provides an opportunity to eliminate inconsistencies in cargo operations, resolve difficulties and reduce errors in monitoring the transportation process. To solve the problem of analyzing railcar and cargo flows through the network of Russian railways, it is proposed to allocate a new data structure that ensures the minimization of the amount of stored information in the target statistics. As transport data increases in quantity and complexity, big data technology is proposed as a solution. The use of the railcar journey repository provides the possibility of monitoring the current transportation process and identifying problematic directions of transportation. The results can be used to plan and forecast freight transportation. The proposed approach to the implementation of the repository greatly simplifies the development of systems for analyzing railcar and train flows. Implemented technologies provide the ability to supplement the architecture with other data and forecast the actual cargo flow on the basis of data from previous periods.

Ключевые слова: 
Russian railways
visual modeling
macro model
company’s performance
railway transportation process
process modeling
international standards
big data technology
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