Information intelligent system of organization and management of arctic sea cargo transportation E Yu Sobolevskaya, N G Levchenko, S V Glushkov Iop Conference Series Materials Science and Engineering, 2020 To organize, support and manage the process of cargo transportation, taking into account the difficult navigation conditions in the Arctic and Subarctic of Russia, an information intelligent system for organizing and managing sea cargo transportation has been developed: architecture of the information intelligent system; a module for calculating the route between two ports, taking into account the ice situation, based on the A-star algorithm for finding the shortest route between two ports; a module for calculating the cost and the number of travel days for sea cargo transportation, taking into account the ice situation, the modules are developed on the basis of fuzzy logic using a Mamdani fuzzy logic model; a module that, on the basis of the first and second modules, calculates a faster or a more cost-effective route depending on the season, taking into account the current ice situation. To check the adequacy of the Mamdani fuzzy logic model, a sample was formed based on the analysis of data from the captain’s voyage reports. Each voyage report contains information on the navigation conditions on the route, which allowed us to create a sample consisting of information on the actual navigation conditions.
Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic N G Levchenko, S V Glushkov, E Yu Sobolevskaya, A P Orlov Journal of Physics Conference Series, 2018 The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.
Development of efficiency module of organization of Arctic sea cargo transportation with application of neural network technologies E Yu Sobolevskaya, S V Glushkov, N G Levchenko, A P Orlov Journal of Physics Conference Series, 2018 The analysis of software intended for organizing and managing the processes of sea cargo transportation has been carried out. The shortcomings of information resources are presented, for the organization of work in the Arctic and Subarctic regions of the Far East: the lack of decision support systems, the lack of factor analysis to calculate the time and cost of delivery. The architecture of the module for calculating the effectiveness of the organization of sea cargo transportation has been developed. The simulation process has been considered, which is based on the neural network. The main classification factors with their weighting coefficients have been identified. The architecture of the neural network has been developed to calculate the efficiency of the organization of sea cargo transportation in Arctic conditions. The architecture of the intellectual system of organization of sea cargo transportation has been developed, taking into account the difficult navigation conditions in the Arctic. Its implementation will allow one to provide the management of the shipping company with predictive analytics; to support decision-making; to calculate the most efficient delivery route; to provide on demand online transportation forecast, to minimize the shipping cost, delays in transit, and risks to cargo safety.
