基于BP神经网络算法的北京市地铁站应急疏散能力仿真评估模型

地铁站的应急疏散能力是地下铁道安全运营设计中非常重要的部分,对于维持社会稳定,保障人民安全具有重大意义.本文利用BP神经网络计算方法和MATLAB软件,选取可能影响地铁站疏散能力的相关因素作为评价指标,建立了应急疏散指标体系,并以北京北三环区域周边地铁站作为主要研究对象,对北京市地铁站应急疏散能力进行了仿真评估,提出了增加疏散通道、疏散楼梯、安全出口等数量,以提高地铁站应急疏散能力等一些可供参考的建议.

Virtual assessment model on emergency evacuation capacity of Beijing subway based on BP neural network algorithm

The emergency evacuation capacity of subway station is a quite important part of safety operation design of subway,with great significance to maintain social stability and ensure people security.In this paper,by applying the BP neural network algorithm and MATLAB software,the index system of emergency evacuation was established by selecting the relative factors that might influence the evacuation capacity of subway station as assessment index.Taking the subway stations around the North 3rd Ring area in Beijing as main objects,the virtual assessment on emergency evacuation capacity of subway station in Beijing was conducted.Some suggestions that can be referenced were put forward,such as increase the quantity of evacuation routes,stairs and exits,so as to improve the emergency evacuation capacity of subway station.