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Modeling and performance analysis of emergency intelligence service process based on stochastic petri nets: A case study of the "7·20″ zhengzhou rainstorm in China
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DOI：10.1016/j.ress.2025.112119.png)
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Abstract
En 中文
Emergency Intelligence Service (EIS) plays a vital role in disaster response by supporting cross-departmental coordination and decision-making. This paper proposes an integrated framework based on Fault Tree Analysis (FTA) and Stochastic Petri Nets (SPN) for modeling and performance analysis of EIS processes under complex disaster scenarios. Potential failure factors in the process are identified through FTA and subsequently transformed into An spn to capture the dynamic behavior of the service flow. Furthermore, Markov chain steady-state analysis is employed to enable quantitative performance evaluation. Using the “7·20″ Zhengzhou catastrophic rainstorm as a case study, the results indicate that intelligence demand matching, material distribution, rescue operations, and service evaluation are the critical bottlenecks in the process. These bottlenecks directly affect overall coordination efficiency and system resilience, while their optimization can reduce casualties, improve rescue effectiveness, and enhance resource allocation.
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