Application of intelligent processing of data flows under conditions of river navigation

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.131599

Keywords:

safety of navigation, electronic navigation, traffic criteria, artificial intelligence, neural network

Abstract

Implementation of a context-oriented approach for intelligent processing of navigation data flows in operation of water vehicles was considered. The initial sample of processing data flows in the conditions of the current pilot navigation method does not correspond to the regularities of functioning of a complex object with the modern instrumental method of navigation. Solution to the problem consists in overcoming difficulties by defining complex problems of the processes that differ from a simple sum of parameters of elements with the same type of multilevel connections.

A method for processing flows of navigation data under continuous mode was proposed. In the process of study, combining of information from multiple sources with finding more accurate and reliable data was considered. The method of estimation of problem solutions is the criterion method where each single alternative is estimated by a specific number (criterion, objective function). Comparison of alternatives was reduced to a comparison of the corresponding numbers. Various variants of the choice of alternatives and criteria of optimality were taken into account: the criteria of Bayes, Wald, Jain, Laplace. The method used is characterized by multicriteria conditions. Methods of decision-making in games with environment, normalization, the use of neural networks based on the context were applied. The architecture of an artificial neural network was constructed.

The study was conducted with the aim of obtaining a stable structure of the system with certain classes of input signals based on artificial neural networks. It is interesting from the theoretical point of view to obtain a parametric variation of the parameters within the specified limits of the optimality criteria. The conducted experiments confirmed efficiency of the use of the proposed methods. The most constructive direction of intelligent processing of the navigational data flow is the context-oriented approach. Implementation of this approach guarantees high level of observance of accuracy criteria in the conditions of river navigation.

An applied aspect of using the results obtained in the process of study is the possibility to abandon the pilotage method of navigation and installation of coastal and floating means of navigation equipment. An important result is derivation of a differentiated mapping of the depth array on an electronic chart. The obtained results give grounds to assert the possibility of introducing the proposed context-oriented approach to real navigation.

Author Biographies

Mikhail Alieinikov, State University of Infrastructure and Technologies Kyrylivs’ka str., 9, Kyiv, Ukraine, 04071

Postgraduate student

Department of Technical Systems and Control Processes in Navigation

Vladymyr Doronin, State University of Infrastructure and Technologies Kyrylivs’ka str., 9, Kyiv, Ukraine, 04071

PhD, Associate Professor

Department of Technical Systems and Control Processes in Navigation

Vladyslav Panin, State University of Infrastructure and Technologies Kyrylivs’ka str., 9, Kyiv, Ukraine, 04071

Doctor of Technical Sciences, Professor, Rector

Illya Tykhonov, State University of Infrastructure and Technologies Kyrylivs’ka str., 9, Kyiv, Ukraine, 04071

PhD, Associate Professor

Department of Navigation and Ship Management

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Published

2018-05-18

How to Cite

Alieinikov, M., Doronin, V., Panin, V., & Tykhonov, I. (2018). Application of intelligent processing of data flows under conditions of river navigation. Eastern-European Journal of Enterprise Technologies, 3(9 (93), 6–18. https://doi.org/10.15587/1729-4061.2018.131599

Issue

Vol. 3 No. 9 (93) (2018): Information and controlling system

Section

Information and controlling system

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Copyright (c) 2018 Mikhail Alieinikov, Vladymyr Doronin, Vladyslav Panin, Illya Tykhonov

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