基于随机Petri网的群体性突发事件情景演变模型

Scenario Evolvement Model of Unexpected Incidents Involving Mass Participation Based on Stochastic Petri Nets

群体性突发事件近几年已严重影响到我国社会和谐和公共安全。本文采用了多案例分析方法提取群体性突发事件的属性,从"事件类型、关键属性、从属属性、环境属性和危害评估属性"对其进行结构化描述。在此基础上,分析群体性突发事件演化过程中的相关属性,利用基于模糊集和随机Petri网的建模分析方法,根据随机Petri网与马尔科夫链的同构关系,构建了群体性突发事件演化的随机Petri网模型和等价马尔科夫链模型。以"池州事件"为例,通过马尔科夫链及其相关数学方法对池州群体性事件不同演化状态进行了情景推演模拟,并分析其中的均衡状态及其变动规律,研究结果表明:群体性突发事件是社会结构性压力超过社会承受阈值时,在导火索事件诱发下群体行为爆发的过程;谣言具有"蝴蝶效应",对群体间消极情绪激化影响显著;群体情绪的相互感染和结构性传导,使群体社会认知产生偏差,导致行为缺乏理性,最终促成群体性事件发生。结合情景推演结果提出了相应的对策建议,为群体性突发事件"情景-应对"提供应急决策支持。

Unexpected incidents involving mass participation have impacted China's social harmony and public safety in recent years.This paper extracts unexpected incident attributes by the approach of multi-case study to describe the unexpected incident structurally from the event type,the key attributes,the secondary attributes,the environment attributes and the hazard assessment attributes. On the basis of the structural description,we analyze the properties of related events in the events chain for the process of unexpected incident,apply the fuzzy sets and stochastic Petri nets to model the unexpected incident,and establish the corresponding Markov chain model based on isomorphic relation between stochastic Petri nets and Markov chain. Then the paper takes different evolutionary status of mass incidents for scenario derivation simulation and studies the equilibrium state and fluctuation pattern of the system for evaluating and improving the system with Markov chain and corresponding mathematics method in the case of'Chi'zhou incident',the main conclusions are the followings: mass incidents are a outbreak process of group behavior with the fuse event when social structural pressures over social tolerance threshold; rumors possess'butterfly effect',and significantly impact on negative emotions between the groups; the group emotional cross contamination and structural transfer,leading to groups social cognition bias and irrational behavior,then eventually mass incidents occurred. Finally,the paper provides decision-making support for monitoring and responding to the unexpected incidents involving mass participation in'scenario-response'.