Analysis of neural networks for predicting time series when assessing industrial safety risks

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).