基于大数据的恐慌群体应急疏散模型

Miao Zhang, Y. Wan-jun, Huai-Lin Zhao, Yu Tian, Jun-Yi Tang, M. Zhang
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引用次数: 1

摘要

为了研究突发事件中恐慌群体行为对人群疏散效率的影响,基于大数据技术理论和蚁群算法构建了人群应急疏散模型。模型中考虑了恐慌因素和恐慌群体因素,使模型更接近实际情况。基于模型计算的复杂性,采用蚁群算法对模型进行求解。研究结果表明,在应急疏散过程中,需要注意关键节点(当前限制区)的疏散,由于疏散路网中疏散人群的恐慌程度对路段的影响不同,应注意关键路段的疏散过程,避免发生拥挤踩踏等事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergency evacuation model of panic group based on Big data
In order to study the effect of panic group behavior on the efficiency of crowd evacuation in emergencies, a crowd emergency evacuation model was constructed based on the theory of big data technology and ant colony algorithm. The panic factor and panic group factor are considered in the model, making the model closer to the actual situation. Based on the complexity of model calculation, the ant colony algorithm is used to solve the model. The research results show that in the emergency evacuation process, attention needs to be paid to the evacuation of key nodes (current restricted areas), and due to the different effects of the panic degree of the evacuated crowd in the evacuation road network on the road sections, attention should be paid to the evacuation process of key road sections to avoid occurrence Crowded stampede and other incidents.
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