铁路客运车站客流监测与预警系统

由于缺乏准确的实时客流数据，铁路客运车站的客运组织一直主要依靠经验来调配设备、人员等所需资源。为此，开发了铁路客运车站客流监测与预警系统，通过有效利用铁路客票预售数据、车站历史客流数据、旅客进出站实时数据、列车正晚点数据等相关数据，建立基于K均值聚类的支持向量回归机客流预测模型，实现车站每日进站客流、分时段进站客流、候车室客流的监测、预测及超限预警，方便车站工作人员随时掌握客流动态，及时根据客流变化进行设备和人员动态调配，更加精准、高效、安全、有序地开展车站客运组织作业，有助于改善车站客运服务水平，提升旅客出行体验。

Passenger flow monitoring and early warning system for railway passenger station

Due to the lack of accurate real-time passenger flow data, passenger traffic organization of railway passenger station has been mainly relying on experience to allocate the equipment, personnel and other required resources. Therefore, the passenger flow monitoring and early warning system for railway passenger station is developed. Through effective use of railway passenger ticket reservation data, historical station passenger flow data, real-time passenger flow data in and out of the station, train delay data and other relevant data, the monitoring, forecasting and over-limit warning of daily passenger flow, time-phased passenger flow of the station and passenger flow in waiting rooms can be realized using a passenger flow prediction support vector regression model based on K-mean clustering, which can facilitate the station staff to grasp the dynamic changes in passenger flow at any time so as to timely deploy the equipment and personnel, thus carrying out the passenger traffic organization operations of the station more accurately, efficiently, safely and orderly, and helping improve the level of passenger service at railway passenger stations and enhancing passenger travel experience.