Modelling and Analysis of Emergency Scenario Evolution System Based on Generalized Stochastic Petri Net

Abstract

Emergency scenario characterization and analysis is an essential approach to describing and understanding the future development of emergencies and assisting in response decision-making. This paper aims to develop a method for emergency evolution analysis in a scenario-based way to improve “scenario response” decision-making. A systematic conceptual framework for emergency scenario evolution (ESE) analysis has been developed based on the domain knowledge of emergency management and the disaster system, combined with the representational ability of the knowledge element model. In addition, a modelling approach for ESE based on the generalized stochastic Petri net (ESEGSPN) is proposed to depict the evolutionary uncertainty through basic control flow and to optimize the parameter uncertainty using fuzzy theory. Finally, the COVID-19 pandemic is used as a case study to show how ESEGSPN works. The results indicate that ESEGSPN can simulate the emergency evolution process, identify critical states and trigger actions, present the evolution trend of typical scenario elements, and assist decision-makers in deploying more targeted emergency responses in dynamically changing situations.