Vol.10, No.1, February 2021.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Forecast Accuracy Evaluation of the Enterprise’s Industrial Safety Integral Risk


Leyla M. Bogdanova, Sergey Ya. Nagibin, Aleksandr S. Chemakin


© 2021 Sergey Ya. Nagibin, 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 10, Issue 1, Pages 45-54, ISSN 2217-8309, DOI: 10.18421/TEM101-06, February 2021.


Received: 14 September 2020.

Revised:   07 December 2020.
Accepted: 26 December 2020.
Published: 27 February 2021.




Autoregressive models represent a time series as a linear dependence of the current value on the retrospective ones. Their feature is the mathematical and statistical base and formalization of the requirements for the parameters’ selection, which makes them relevant and effective. The article describes an algorithm for analyzing time series representing changes in the integral risk indicator and its modeling using various autoregressive models with subsequent comparison of their adequacy and quality evaluation of the resulting forecast. It is shown that with the help of this class models, it is possible to build a forecast for a time period sufficient to make a decision on preventing accidents at complex infrastructure facilities.


Keywords –integral risk indicator, time series forecasting, industrial safety, mathematical modeling, time series analysis, risk-based approach, forecasting results evaluation.



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