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

被引:0
作者
Naili M. [1 ]
Bourahla M. [2 ]
Naili M. [1 ]
机构
[1] Department of Computer Science, University of Biskra, Biskra
[2] Department of Computer Science, University of M'Sila, M'Sila
[3] Department of Computer Science, University of Bordj Bou Arreridj, Bordj Bou Arreridj
来源
International Journal of Simulation and Process Modelling | 2019年 / 14卷 / 01期
关键词
ABM; Agent-based modelling; Dynamic data mining; Dynamic models; Evacuation building system; Modelling; Monte Carlo simulation; Simulation; Stability; Steady state;
D O I
10.1504/IJSPM.2019.097702
中图分类号
学科分类号
摘要
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. Copyright © 2019 Inderscience Enterprises Ltd.
引用
收藏
页码:1 / 16
页数:15
相关论文
共 50 条
  • [31] Agent-Based Simulation in the Study of Social Dilemmas
    N.M. Gotts
    J.G. Polhill
    A.N.R. Law
    Artificial Intelligence Review, 2003, 19 : 3 - 92
  • [32] Optimizing evacuation paths using agent-based evacuation simulations and reinforcement learning
    Takabatake, Tomoyuki
    Asai, Keito
    Kakuta, Hiroki
    Hasegawa, Nanami
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2025, 117
  • [33] THE STOCHASTIC SIMULATION BASED ON THE MONTE CARLO METHOD
    Diaconu, Aurelian
    METALURGIA INTERNATIONAL, 2012, 17 (05): : 162 - 165
  • [34] Monte Carlo simulation model of OCT system based on confocal mode
    Wu, KJ
    Li, G
    Lin, L
    Yu, QL
    PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 2, 2004, : 1096 - 1101
  • [35] Improving human behaviour in macroscale city evacuation agent-based simulation
    Barnes, Beth
    Dunn, Sarah
    Pearson, Christopher
    Wilkinson, Sean
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2021, 60
  • [36] An interdisciplinary agent-based evacuation model: integrating the natural environment, built environment, and social system for community preparedness and resilience
    Chen, Chen
    Koll, Charles
    Wang, Haizhong
    Lindell, Michael K.
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2023, 23 (02) : 733 - 749
  • [37] Power system stochastic transient stability assessment based on Monte Carlo simulation
    Liu, Jiayu
    Liu, Jun
    Zhang, Jie
    Fang, Wanliang
    Qu, Longchu
    JOURNAL OF ENGINEERING-JOE, 2019, (16): : 1051 - 1055
  • [38] Hull girder reliability using a Monte Carlo based simulation method
    Gaspar, B.
    Guedes Soares, C.
    PROBABILISTIC ENGINEERING MECHANICS, 2013, 31 : 65 - 75
  • [39] Impact of Passenger Group Dynamics on an Airport Evacuation Process Using an Agent-Based Model
    Cheng, Lin
    Reddy, Vikas
    Fookes, Clinton
    Yarlagadda, Prasad K. D. V.
    2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), VOL 2, 2014, : 161 - 167
  • [40] A reliability-based optimization method using sequential surrogate model and Monte Carlo simulation
    Li, Xu
    Gong, Chunlin
    Gu, Liangxian
    Jing, Zhao
    Fang, Hai
    Gao, Ruichao
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 59 (02) : 439 - 460