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An Evacuation Model Based on the Improved Particle Swarm Optimization

机译:基于改进粒子群算法的疏散模型

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In recent years, the unexpected factors leading to frequent accidents which causing heavy casualties and economic losses. Therefore, how to make use of computer technology to simulate the evacuation process has an important practical significance. In this paper, we propose a new model for evacuation. Based on the traditional particle swarm algorithm, we revise the inertia weight of the algorithm to balance the global and local search ability according to the aggregation degree of the population. Taking the interaction between individual and others, individual and obstacles or wall into account, we introduce the social force model to simulate this phenomenon and use it as a collision resolution strategy. Then, we combine the improved PSO-based model with modified Social Force Model to form the velocity updating rule. In the end, through simulation and analyzation, we testify the modified model is very effective.
机译:近年来,意外因素导致事故频发,造成重大人员伤亡和经济损失。因此,如何利用计算机技术模拟疏散过程具有重要的现实意义。在本文中,我们提出了一种新的疏散模型。在传统粒子群算法的基础上,我们对算法的惯性权重进行了修正,以根据种群的聚集程度来平衡全局和局部搜索能力。考虑到个人与他人,个人与障碍物或墙壁之间的相互作用,我们引入社会力量模型来模拟这种现象并将其用作冲突解决策略。然后,我们将改进的基于PSO的模型与改进的社会力量模型相结合,以形成速度更新规则。最后,通过仿真和分析,证明了改进后的模型是非常有效的。

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