On regression approach to forecasting passenger demand in railway transport
Due to the fact that the autocorrelation of time series of passenger demand under normal conditions is, as a rule, practically undeveloped, traditional forecasting methods based on taking into account autocorrelation dependences are not effective enough. The article proposes a direct accounting of t...
| Main Authors: | , |
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| Format: | Article |
| Language: | Russian |
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Joint Stock Company «Railway Scientific and Research Institute»
2021-04-01
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| Series: | Вестник Научно-исследовательского института железнодорожного транспорта |
| Subjects: | |
| Online Access: | https://www.journal-vniizht.ru/jour/article/view/498 |
| _version_ | 1797872263735803904 |
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| author | G. L. Venediktov V. M. Kochetkov |
| author_facet | G. L. Venediktov V. M. Kochetkov |
| author_sort | G. L. Venediktov |
| collection | DOAJ |
| description | Due to the fact that the autocorrelation of time series of passenger demand under normal conditions is, as a rule, practically undeveloped, traditional forecasting methods based on taking into account autocorrelation dependences are not effective enough. The article proposes a direct accounting of the main factor affecting the accuracy of forecasting, namely the factor of seasonal heterogeneity of demand. This accounting is made on the basis of polynomial regression for the time dependence of demand. A specific design example demonstrates the comparative advantages of this approach to assessing the forecast of demand for rail transport.The regression approach is applied to the weekly averaged demand metrics for the time domain, where these metrics are considered known from the sales history. If there is a weekly demand heterogeneity in the forecast zone, an algorithm is proposed to restore such heterogeneity from the initial data.The forecast accuracy based on the proposed method is compared with the results achieved on the basis of the ARIMA model, which reveals, according to preliminary estimates, fairly high accuracy parameters. It is shown on the calculated examples that for the series of demand, which can be considered typical for the sphere of passenger traffic, the regression approach gives the forecast accuracy higher than the ARIMA model. The reasons are considered, due to which, for typical series of passenger demand, the regression approach can be considered as more promising than methods that include taking into account autocorrelation. |
| first_indexed | 2024-04-10T00:56:01Z |
| format | Article |
| id | doaj.art-2c9f4945fe28468d9d788dc0e9363f83 |
| institution | Directory Open Access Journal |
| issn | 2223-9731 2713-2560 |
| language | Russian |
| last_indexed | 2024-04-10T00:56:01Z |
| publishDate | 2021-04-01 |
| publisher | Joint Stock Company «Railway Scientific and Research Institute» |
| record_format | Article |
| series | Вестник Научно-исследовательского института железнодорожного транспорта |
| spelling | doaj.art-2c9f4945fe28468d9d788dc0e9363f832023-03-13T10:14:34ZrusJoint Stock Company «Railway Scientific and Research Institute»Вестник Научно-исследовательского института железнодорожного транспорта2223-97312713-25602021-04-01801455210.21780/2223-9731-2021-80-1-45-52325On regression approach to forecasting passenger demand in railway transportG. L. Venediktov0V. M. Kochetkov1Общество с ограниченной ответственностью «Экспресс-Л» (ООО «Экспресс-Л»)Общество с ограниченной ответственностью «Экспресс-Л» (ООО «Экспресс-Л»)Due to the fact that the autocorrelation of time series of passenger demand under normal conditions is, as a rule, practically undeveloped, traditional forecasting methods based on taking into account autocorrelation dependences are not effective enough. The article proposes a direct accounting of the main factor affecting the accuracy of forecasting, namely the factor of seasonal heterogeneity of demand. This accounting is made on the basis of polynomial regression for the time dependence of demand. A specific design example demonstrates the comparative advantages of this approach to assessing the forecast of demand for rail transport.The regression approach is applied to the weekly averaged demand metrics for the time domain, where these metrics are considered known from the sales history. If there is a weekly demand heterogeneity in the forecast zone, an algorithm is proposed to restore such heterogeneity from the initial data.The forecast accuracy based on the proposed method is compared with the results achieved on the basis of the ARIMA model, which reveals, according to preliminary estimates, fairly high accuracy parameters. It is shown on the calculated examples that for the series of demand, which can be considered typical for the sphere of passenger traffic, the regression approach gives the forecast accuracy higher than the ARIMA model. The reasons are considered, due to which, for typical series of passenger demand, the regression approach can be considered as more promising than methods that include taking into account autocorrelation.https://www.journal-vniizht.ru/jour/article/view/498пассажирские перевозкипрогноз пассажирского спросаавторегрессияarimaполиномиальная регрессияавтокорреляциясезонная неоднородность спроса |
| spellingShingle | G. L. Venediktov V. M. Kochetkov On regression approach to forecasting passenger demand in railway transport Вестник Научно-исследовательского института железнодорожного транспорта пассажирские перевозки прогноз пассажирского спроса авторегрессия arima полиномиальная регрессия автокорреляция сезонная неоднородность спроса |
| title | On regression approach to forecasting passenger demand in railway transport |
| title_full | On regression approach to forecasting passenger demand in railway transport |
| title_fullStr | On regression approach to forecasting passenger demand in railway transport |
| title_full_unstemmed | On regression approach to forecasting passenger demand in railway transport |
| title_short | On regression approach to forecasting passenger demand in railway transport |
| title_sort | on regression approach to forecasting passenger demand in railway transport |
| topic | пассажирские перевозки прогноз пассажирского спроса авторегрессия arima полиномиальная регрессия автокорреляция сезонная неоднородность спроса |
| url | https://www.journal-vniizht.ru/jour/article/view/498 |
| work_keys_str_mv | AT glvenediktov onregressionapproachtoforecastingpassengerdemandinrailwaytransport AT vmkochetkov onregressionapproachtoforecastingpassengerdemandinrailwaytransport |