Analysis of Neural Networks for Predicting Time Series When Assessing Industrial Safety Risks
Analysis of Neural Networks for Predicting Time Series When Assessing Industrial Safety Risks
Author(s): Sergey Ya. Nagibin, Dmitry I. LoskutovSubject(s): ICT Information and Communications Technologies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Coefficient of determination; industrial safety; Kullback Leibler divergence; monitoring; neural network; risk based approach; Zodiac software;
Summary/Abstract: The paper describes the choice of an artificial neural network (ANN), the most effective for use in problems of modeling the behavior of complex dynamic systems with the subsequent solution of the forecast problem. The choice is made to implement a risk-based approach in the domestic trusted innovation umbrella system «Zodiac» when monitoring the industrial safety of the enterprises of the Fuel and Energy Complex (FEC).
Journal: TEM Journal
- Issue Year: 9/2020
- Issue No: 2
- Page Range: 477-483
- Page Count: 7
- Language: English
