Methods to Forecast Transport Systems Development under Modern Conditions

Author:

Kiselenko A. N.1,Sundukov E. Yu.1,Tarabukina N. A.1

Affiliation:

1. Institute of Socio-Economic and Energy Problems of the North of the Federal Research Centre «Komi Scientific Centre of Ural Branch of Russian Academy of Sciences»

Abstract

The objective of the work is to study methods for forecasting transport systems development and determine their suitability under economic instability conditions.The modern methodology for forecasting the development of regional transport systems includes expert and formal methods, methods of active and passive forecasting.The use of expert systems, scenario forecasting and strategic planning can be mentioned as promising areas.Scenario planning is more adapted to non-linear transformations in the economy than traditional linear planning. In traditional planning, the past explains the present, in scenario planning, the future is the meaning of the present, the future is created.The variety and instability of statistical indicators encourages creation of hybrid systems of forecasting models. They are based on regression models, as well as on intelligent models, including artificial neural networks, analytical networks, etc., which are complemented by scenario forecasting.The identification of the main factors that determine the functioning of the transport network of the European and Ural Arctic facilitated the choice of methods for forecasting its development. The main factors negatively affecting the development of the transport network of the region under the study are the insufficiency of freight flows in the ports; insufficient capacity of seaports’ access roads; political, social, natural-climatic, and other risks.The example of the Northern Sea Route (NSR) illustrates the use of a hybrid system of forecasting models to obtain possible values of traffic volumes. Based on the analysis of regression models and the study of the possibility of achieving the target traffic volume by 2024, it was concluded that this model is basically acceptable for forecasting the volume of goods transported along the NSR.

Publisher

FSBEO HPE Moscow State University of Railway Engineering (MIIT)

Subject

General Medicine

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