Automation of acceptance of wagons for transportation: control system and neural network model

Purpose: the article examines the problem areas of interaction between the carrier and the cargo owner, as well as existing methods for improving it. A solution to the problem of labor-intensive information support for freight transportation is proposed using intelligent information technology. Its structure has been determined, the system for managing the process of accepting a wagon for transportation has been improved, and a decision support system in the field of rail freight transportation has been developed. The life cycle diagram of the transportation process, built using the IDEF0 functional modeling methodology, reflects the influence of intelligent information technology on all components during its implementation. The practical aspect of implementation is represented by a software product based on a neural network model complex. The results of model experiments in laboratory conditions and tests in real conditions at the Oktyabrskaya Railway test site are presented, which showed a significant reduction in the time spent on accepting a car for transportation and the influence of the human factor, which in the future reduces the cost of freight transportation. Methods: the study uses methods of system analysis, transportation management theory, neural network modeling and synthesis of existing models. Results: a technology has been proposed and specific tools have been developed to improve the quality of information support for rail freight transportation. Practical significance: the implementation of the developed solutions will automate information support for rail freight transportation and data exchange between the carrier and the shipper.