Stability-based model for evacuation system using agent-based social simulation and Monte Carlo method

Makhlouf Naili, M. Bourahla, Mohamed Naili
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引用次数: 8

Abstract

The agent-based modelling is used for modelling many complex dynamic systems, especially those including autonomous individuals such as human beings' societies, animals' societies, robots, insects' societies, etc. Evacuation systems such as those needed for supermarket buildings are considered as complex dynamic systems. In these systems, we have to deal with the problem of rescuing a high number of people of different ages, sex, physical characteristics, etc. Furthermore, this process mostly runs in buildings with different constraints like locations of the rows of shelves, exit gates, etc. On one hand, in order to deal with disasters such as fire propagation, studying this kind of system using a dynamic model has a great importance in order to avoid the maximum of casualties. On the other hand, the model that represents this kind of system must take into account several factors such as time, the building's characteristics and people's characteristics. In this study, an agent-based model has been designed to visualise the dynamic system behaviour via these internal entities that often interact. Additionally, we use some dynamic data mining methods such as Monte Carlo method to calculate the stable characteristics of this model via probabilistic approach.
基于智能体的社会仿真和蒙特卡罗方法的疏散系统稳定性模型
基于agent的建模被用于许多复杂动态系统的建模,特别是那些包含自主个体的系统,如人类社会、动物社会、机器人社会、昆虫社会等。超市建筑物的疏散系统被认为是复杂的动态系统。在这些系统中,我们必须处理拯救大量不同年龄、性别、身体特征等的人的问题。此外,这一过程主要在具有不同约束条件的建筑物中运行,如货架排的位置,出口门等。一方面,为了应对火灾传播等灾害,利用动态模型对这类系统进行研究,以避免造成最大的人员伤亡,具有重要意义。另一方面,代表这种系统的模型必须考虑到时间、建筑特点和人的特点等几个因素。在本研究中,设计了一个基于代理的模型,通过这些经常相互作用的内部实体来可视化动态系统行为。此外,我们还利用蒙特卡罗方法等动态数据挖掘方法,通过概率方法计算该模型的稳定特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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