FEATURES OF TIME SERIES USING FOR ESTIMATION OF FLUCTUATIONS OF CAR TRAFFIC VOLUMES AT THE RAILWAY DIVISION POINTS

The study of intra-annual dynamics of car traffic volumes, handed over at the railway division points of the Russian Federation is an essential part of the long-range prediction, planning and analysis of transport activity. The increase in the regularity of pace of the production process is directly related to the assessment of the unevenness of car traffic volumes. The ability to predict the unevenness of the transport process, as well as uneven loading with the establishment of relevant indicators is a key issue in the regularity of pace of transport operation. The presented article analyzes the structure of time series of fluctuations in car traffic volumes at the railway division points in order to further build a model for predicting fluctuations in car traffic volumes and, in the future, loading cargo to the ports of the Far East. This methodology is based on the analysis of the structure of time series of fluctuations in car traffic volumes handed over at the railway division points and moving further towards seaports with the subsequent construction of a mathematical model of cargo loading, on the basis of which it will subsequently be possible to predict the loading for the coming year. The presented work considers an analysis of the structure of time series of fluctuations in car traffic volumes and proposes models for the subsequent construction of a prediction. It also applies a systemic approach to solving the problem of predicting the car traffic volume. The proposed tools make it possible to develop prediction models to assess the seasonal unevenness of cargo loading in the direction of seaports. All this will contribute to the improvement of logistics planning of transportation and will give a further impetus to the development of the industry. The whole range of activities consists in the possibility of constructing predictive models for the production unit of the Russian Railways holding. In addition, it will be possible to update the structure of the network’s operational indicators.