Name
Abstract | ||
|---|---|---|
In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model based on the improved artificial swarm algorithm. In this article, the cellular automata (CA) model is used to establish the evacuation environment, and then the artificial bee colony (ABC) algorithm is used to simulate the crowd evacuation. However, due to too many obstacles existing in the neighboring cells of some position, the individual in that position have to wait. If the distance equation is used to calculate the fitness, it may cause other individuals to choose these positions as new position and repeat the same mistake above. To reduce the occurrence of such cases, we improve the fitness function of the ABC algorithm. In the fitness function, the factors of attraction and repulsion force in social force model are introduced. And on the basis of the ABC algorithm, we propose the visual employed bee. The visual employed bee leads the onlooker bee to evacuate, so as to improve the efficiency of evacuation. The research results of this article can provide ideas for evacuation modeling and useful guidance for formulating evacuation strategies to reduce evacuation time and disaster losses. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IDAACS.2019.8924263 | 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) |
Keywords | Field | DocType |
artificial bee colony algorithm,cellular automaton model,evacuation,visual employed bee,fitness function | Cellular automaton,Artificial bee colony algorithm,Social force model,Emergency evacuation,Swarm behaviour,Computer science,Crowd evacuation,Fitness function,Repulsion force,Artificial intelligence,Machine learning | Conference |
Volume | ISBN | Citations |
1 | 978-1-7281-4070-4 | 0 |
PageRank | References | Authors |
0.34 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinlu Zong | 1 | 0 | 0.34 |
| Jiayuan Du | 2 | 0 | 0.34 |
| Wei Liu | 3 | 11 | 21.81 |
| Lu Zhang | 4 | 0 | 1.01 |
| Qian Huang | 5 | 0 | 0.34 |