摘要
针对室内空间的行人流疏散过程,在元胞自动机的基础上,利用类电磁法和模糊神经网络建立了一种新的行人流优化模型.该模型首先基于静态影响因素和动态影响因素给出了行人移动概率的计算公式,以及行人流演化过程.同时,结合疏散时间、系统平均速度、出口处流率给出了目标优化函数,并通过类电磁法和模糊神经网络对上述目标函数进行求解.最后,利用仿真平台进行实验,深入分析了疏散时间、出口宽度和初始行人密度之间的关系.结果表明,疏散时间与出口宽度呈现负相关,并且适当提高系统平均速度有利于降低疏散时间.
In order to effectively depict the pedestrian evacuation process, based on the cellular automaton, a novel evacuation model was proposed by electromagnetism mechanism and fuzzy neural network. Combined the static factor and dynamic factor, the calculation formula of transition probability and evacuation strategy were given. Meanwhile, the optimization function is given with evacuation time, average system velocity and flow rate, and it is solved by electromagnetism mechanism and fuzzy neural network. At last, experiments were conducted with the simulation platform to study the relationships of e- vacuation time, exit width as well as initial pedestrian density. The results showed that evacuation time had a negative correlation with exit width, and an appropriate increasing for average system velocity would reduce the evacuation time.
出处
《四川大学学报(自然科学版)》
CAS
CSCD
北大核心
2016年第4期753-758,共6页
Journal of Sichuan University(Natural Science Edition)
基金
四川省科技厅应用基础项目(2015JY0213)
四川省教育厅创新团队项目(15TD0038)
关键词
行人流
元胞自动机
类电磁法
模糊神经网络
Pedestrian
Cellular automaton
Electromagnetism mechanism
Fuzzy neural network