Risk propagation and evolution analysis of multi-level handlings at automated terminals based on double-layer dynamic network model

Abstract

The propagation and evolution of risks in the system adversely affects the safety of automated terminal handlings. Therefore, it is necessary to explore the formation and development process of handling risks, predict the path and pattern of risk propagation and summarize the evolution features to improve the efficiency of multi-level handlings at automated terminals (ATMH). This paper proposes a double-layer dynamics risk propagation and evolution model. First, a complex network of risk relationships is established, and the Gillespie algorithm is employed to simulate the risk propagation dynamics based on the metric of state transition value and the dynamic mean-field theory. Next, an evolution hypernetwork is constructed and the average smooth hyperdegree distribution is derived using Poisson process and continuity methods. The simulation results show that the risk propagation link group obtained by the empirical testing is credible. The theoretical predictions of risk evolution agree well with the numerical simulations. The greater the probability of risk propagation, the more active the evolution. The model provides a certain theoretical reference for the risk management of automated terminals.