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Dynamic propagation model of crowd panic based on Shanoon's entropy theory under COVID-19 epidemic situation

机译:基于Covid-19流行情况下Shanoon熵理论的人群恐慌动态传播模型

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Pedestrian merging flow in the crowd gathering public places are the common movement nodes of crowd kinematics merging and psychological panic transmission. There are stochastic turbulences, disturbances and density fluctuations in the crowd merging area, with high risk of pedestrian stampede events. Based on the dynamics model of crowd merging, this study considers the psychological characteristics of the escape panic in the normal disaster conditions of the crowd in the cross-passages and the epidemic panic psychological characteristics under the public health events. With the introduction of Shanoon's information entropy theory, panic entropy is applied to measure the degrees of transient panic in the fluid grid area of the crowd, the overall transient disorder of the crowd, and the dynamic relationship with time and space changes. This study comprehensively considers the characteristics of conventional escape panic and epidemic panic, defines protective relaxation factors, forms a dynamic model of escape panic propagation, and provides a scientific theoretical basis for crowd evacuation guidance under COVID-19 epidemic situation.
机译:在人群聚集的行人流量合并公共场所是人群运动合并和心理恐慌传输的通用移动节点。有随机的动荡,干扰和密度波动在人群中汇流区,与行人踩踏事件的高风险。基于人群合并的动力学模型,这项研究考虑了逃逸恐慌的心理特点,在跨通道人群的正常灾情和疫情下的公共卫生事件的恐慌心理特征。随着引进Shanoon的信息熵理论,恐慌熵应用于测量瞬态程度的恐慌在人群中,人群的总体短暂的疾病,且随时间和空间变化的动态关系的流体网格区域。本研究综合考虑常规逃生恐慌和疫情恐慌的特点,确定保护松弛因子,形成逃生恐慌传播的动态模型,并提供了COVID-19疫情下人群疏散引导科学的理论依据。

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