Forecast Accuracy Evaluation of the Enterprise’s Industrial Safety Integral Risk
Forecast Accuracy Evaluation of the Enterprise’s Industrial Safety Integral Risk
Author(s): Leyla M. Bogdanova, Sergey Ya. Nagibin, Aleksandr S. ChemakinSubject(s): Business Economy / Management
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: integral risk indicator; time series forecasting; industrial safety; mathematical modeling; time series analysis; risk-based approach; forecasting results evaluation.
Summary/Abstract: 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.
Journal: TEM Journal
- Issue Year: 10/2021
- Issue No: 1
- Page Range: 45-54
- Page Count: 10
- Language: English
