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An Evacuation Model Based on the Improved Particle Swarm Optimization

机译:一种基于改进粒子群优化的疏散模型

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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,意外因素导致频繁发生意外,导致严重伤亡和经济损失。因此,如何利用计算机技术来模拟疏散过程具有重要的实际意义。在本文中,我们提出了一种疏散模型。基于传统的粒子群算法,我们根据群体的聚合程度来修改算法的惯性权重平衡全球和本地搜索能力。考虑个人和其他人,个人和障碍物或墙壁之间的互动,我们介绍了社会力量模型来模拟这种现象,并将其作为碰撞解决策略。然后,我们将改进的PSO的模型与修改的社会力模型相结合,形成了速度更新规则。最后,通过仿真和分析,我们证明了修改模型非常有效。

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