Abstract
Dynamic processes in various fields exhibit risk coupling phenomena, but existing risk analysis studies tend to ignore the risk coupling effects of dynamic scenarios. Considering the principles of digitization, objective quantification, and the full process that should be adopted in the risk coupling analysis, an integrated risk coupling analysis framework is proposed. Specifically, the weighted Eclat algorithm is used to mine the risk association rules, then the key risk factors are extracted by social network analysis, and the stochastic Petri net is used to complete the construction, simulation, and evolution of accident scenarios. This universal framework can analyze the risk phenomena of accident scenario evolution in a process-oriented manner and decouple risks based on key risk factors and disconnect the chain of the accident scenario evolution process. Finally, the proposed framework is applied to the coupled analysis of fire risk in Chinese urban communities to verify its feasibility and scientific validity.
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