Selecting an optimal model for forecasting the volumes of railway goods transportation
- 作者: Rudakov K.V.1, Strizhov V.V.1, Kashirin D.O.1, Kuznetsov M.P.2, Motrenko A.P.2, Stenina M.M.2
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隶属关系:
- Dorodnicyn Computing Centre
- Moscow Institute of Physics and Technology
- 期: 卷 78, 编号 1 (2017)
- 页面: 75-87
- 栏目: System Analysis and Operations Research
- URL: https://journals.rcsi.science/0005-1179/article/view/150516
- DOI: https://doi.org/10.1134/S0005117917010064
- ID: 150516
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详细
Consideration was given to selection of an optimal model of short-term forecasting of the volumes of railway transport from the historical and exogenous time series. The historical data carry information about the transportation volumes of various goods between pairs of stations. It was assumed that the result of selecting an optimal model depends on the level of aggregation in the types of goods, departure and destination points, and time. Considered were the models of vector autoregression, integrated model of the autoregressive moving average, and a nonparametric model of histogram forecasting. Criteria for comparison of the forecasts on the basis of distances between the errors of model forecasts were proposed. They are used to analyze the models with the aim of determining the admissible requests for forecast, the actual forecast depth included.
作者简介
K. Rudakov
Dorodnicyn Computing Centre
编辑信件的主要联系方式.
Email: rudakov@ccas.ru
俄罗斯联邦, Moscow
V. Strizhov
Dorodnicyn Computing Centre
Email: rudakov@ccas.ru
俄罗斯联邦, Moscow
D. Kashirin
Dorodnicyn Computing Centre
Email: rudakov@ccas.ru
俄罗斯联邦, Moscow
M. Kuznetsov
Moscow Institute of Physics and Technology
Email: rudakov@ccas.ru
俄罗斯联邦, Dolgoprudnyi
A. Motrenko
Moscow Institute of Physics and Technology
Email: rudakov@ccas.ru
俄罗斯联邦, Dolgoprudnyi
M. Stenina
Moscow Institute of Physics and Technology
Email: rudakov@ccas.ru
俄罗斯联邦, Dolgoprudnyi
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