1. Proceedings
  2. I3M
  3. 2018
  4. HMS
  5. 10.46354/i3m.2018.hms.003

On the real time logistics monitoring system development using artificial neural network

  • a Dmitriy Petrovskiy  , 
  • b Aleksandr Barashkov  , 
  • c Vladislav Sobolevsky  , 
  • d,e Boris Sokolov ,  
  • f Vjacheslav Pjatkov  
  • a,b NRUHSE(SPb) — National Research University Higher School of Economics (St. Petersburg), Kantemirovskaya Street 3A, St. Petersburg, 194100, Russia
  • c,d SPIIRAS— St. Petersburg Institute of Informatics and Automation, Russian Academy of Sciences, 14th line 39, St. Petersburg, 199178, Russia
  • e ITMO University— St. Petersburg National Research University of Information Technologies, Mechanics and Optics,  13 Gdanovskaya str., St. Petersburg, 197198, Russia
  • f Military-space academy, Gdanovskaya str., 13, St. Petersburg, 197198, Russia
Cite as
D. Petrovskiy, A. Barashkov, V. Sobolevsky, B. Sokolov, V. Pjatkov (2018). On the real time logistics monitoring system development using artificial neural network. Proceedings of the 20st International Conference on Harbor, Maritime and Multimodal Logistic Modeling & Simulation (HMS 2018), pp. 14-20. DOI: https://doi.org/10.46354/i3m.2018.hms.003

Abstract

In this article, we consider the creation of a monitoring system for observing the parameters of logistics systems in real time in the conditions of data deficit. Our approach to the creation of such a monitoring system is based on the use of artificial neural networks for the classification of information entering the system. As well, the apparatus of colour stochastic Petri nets were used for data generation that is necessary for training the neural network.

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