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Evacuation Behaviors and Link Selection Strategy Based on Artificial Fish Swarm Algorithm

机译:基于人工鱼群算法的避难行为与选路策略

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Frequent accidents are taken in public places in recent years, causing heavy casualties and economic losses. It is necessary for us to research effective evacuation. Provide evacuation route guidance strategy for the evacuated individuals is the key for emergency evacuation. This paper proposes a evacuation model based on Artificial Fish Awarm Algorithm (AFSA). Define the evacuee as an intelligent artificial fish and utilize the preying behavior, swarming behavior and following behavior of artificial fish swarm to simulate the mental activity, path selection, behavior preference of individuals. The model embody the characteristics of evacuation rules and uncertainties in the process and we can get the optimum path planning. In this paper, we take Zhuankou Stadium in Wuhan Hubei as the experiment environment, to conduct a research of the simulation of evacuation process under emergency. The results of simulations show that this method can and balance the congestion and improve the efficiency and fidelity of evacuation, compared with existing algorithm.
机译:近年来,在公共场所经常发生事故,造成大量人员伤亡和经济损失。我们有必要研究有效的疏散措施。为被疏散人员提供疏散路线指导策略是紧急疏散的关键。本文提出了一种基于人工鱼群算法的疏散模型。将撤离人员定义为智能人工鱼,并利用人工鱼群的捕食行为,蜂群行为和跟随行为来模拟个体的心理活动,路径选择和行为偏好。该模型体现了疏散规则的特点和过程中的不确定性,我们可以得到最佳的路径规划。本文以湖北省武汉市kou口体育馆为实验环境,对应急疏散过程进行了仿真研究。仿真结果表明,与现有算法相比,该方法可以均衡拥塞,提高疏散效率和保真度。

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