摘要
把建筑结构参数、火灾探测系统的烟气状态参数和表征人群行为特征的人群密度参数通过数据融合处理形成统一的知识表征形式,采用T-S模糊神经网络构建多参数智能疏散诱导系统模型,给出疏散人员选择出口或路径的概率表达式。在"黑屋"实验平台上,进行不同特征人群的疏散实验,对系统功能进行实验验证。结果表明:该系统能够缩短疏散时间,提高疏散效率。
T-S fuzzy neural network was used to construct the multi-parameter intelligent evacuation guidance system model,where the structure parameters,smoke parameters of fire detection system and population density of crowd behavior characteristics formed unified knowledge representation by fuzzy processing.The probability function of evacuees choosing exports or evacuation paths was given.Organizing evacuation experiment of various characteristics crowd in ＂black room＂ experimental platform,the system function was verified.The results showed that the system can shorten the evacuation time,and then improve the efficiency of evacuation.
出处
《消防科学与技术》
CAS
北大核心
2014年第6期662-666,共5页
Fire Science and Technology
基金
国家自然科学基金资助项目(60874003)
河北省自然科学基金项目(601260)
关键词
火灾
疏散
建筑智能化
智能疏散诱导系统
动态标志路径
T-S模糊神经网络
fires
evacuation
intelligent buildings
intelligent evacuation guidance system
dynamic identifying paths
t-s fuzzy neural network
