Fuzzy neural network based scenario features extraction and mapping model for crowd evacuation stability analysis

被引：2
|
作者：
Zhao, Rongyong [1 ]
Liu, Qiong [1 ]
Li, Cuiling [2 ]
Dong, Daheng [1 ]
Hu, Qianshan [1 ]
Ma, Yunlong [1 ]
机构：
[1] Tongji Univ, CIMS Res Ctr, Shanghai 201804, Peoples R China
[2] Tongji Univ, Coll Elect & Informat Engn, Shanghai 201804, Peoples R China
来源：
2018 INTERNATIONAL SEMINAR ON COMPUTER SCIENCE AND ENGINEERING TECHNOLOGY (SCSET 2018) | 2019年 / 1176卷
基金：
上海市自然科学基金; 中国国家自然科学基金;
关键词：
D O I：
10.1088/1742-6596/1176/3/032022
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The scenario features of large-scale crowd evacuation are complex and uncertain, leading to difficulties in making intelligent decisions for crowd evacuation stability. Therefore, this paper utilizes a fuzzy neural network method to analyze and extract main crowd scenario features. Subsequently, the stability characteristics as evacuation historical backtracking can be the attributes for evacuation stability judgment. Finally, we can obtain mechanism causes of instability and state evolution law of crowd evacuation, to intervene and guide the large-scale crowd evacuation.
引用
收藏
页数：5
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