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Quantitative Network Analysis for Passenger Pattern Recognition An Analysis of Railway Stations

机译：乘客模式识别的定量网络分析铁路站分析

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As recent attacks in trains and train stations show, the protections of such critical infrastructure plays a major role for public decision makers. Thereby, security installations in the railway network are a frequently discussed topic. Especially the need for an open system demands for technologies that do not influence or delay passenger flows. This also leads to the question of optimal placement of security installations such as smart camera systems or stand-off detectors. For answering this question we observed passenger flows in the Munich central station. The observation data was transferred into a quantitative network and analyzed using various measures. With its help, critical parameter constellations can be identified and investigated in detail. Furthermore we are able to identify special groups of passengers and the differences in their behavior.
机译：随着最近的火车和火车站展示的攻击，这些关键基础设施的保护对公共决策者发挥着重要作用。因此，铁路网络中的安全装置是经常讨论的主题。特别是对不影响或延迟乘客流量的技术的开放系统需求。这也导致了智能摄像机系统或脱扣检测器等安全装置最佳放置问题。回答这个问题，我们观察了慕尼黑中央车站的乘客流动。观察数据被转移到定量网络中并使用各种措施进行分析。利用其帮助，可以详细识别和研究临界参数星座。此外，我们能够识别特殊的乘客群体和行为的差异。

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