Vol.9, No.3, August 2020.                                                                                                                                                                                ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Contextual Approach to Industrial Situation Recognition


V.N. Shepel`, N.V. Speshilova, V.A. Tripkosh, R.R. Rakhmatullin


© 2020 N.V. Speshilova, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 3, Pages 944-950, ISSN 2217-8309, DOI: 10.18421/TEM93-15, August 2020.


Received: 06 December 2019.

Revised:   16 May 2020.
Accepted: 25 May 2020.
Published: 28 August 2020.




The article describes the development of multifaceted and efficient approaches to the context information analysis for synthesis of industrial situations context recognition algorithm in automated management systems within the enterprises. The probability theory method and method of statistical analysis, decision theory method, methods of algorithm and combination theory were used while researching. The research resulted in the development of new approaches to the context information analysis framework for pattern recognition which enables us to identify the procedure of contextual recognition for synthesis of working industrial situation recognition algorithm. A correspondence between the recognition error rate and the guaranteed recognition threshold, which can be used for setting up the automated context-based recognition systems, was analytically obtained during the research.


Keywords –Enterprise, industrial situation recognition, contextual approach, contextual information.



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