摘要
近年来,随着交通运输的不断发展,乘坐飞机人数越来越多,而出租车成为乘客们离开机场的主要交通工具之一。为研究机场出租车的流量情况,通过寻找分析指标来建立出租车司机在机场的决策模型,帮助机场对打车乘客和机场出租车进行合理规划,文章通过收集某日机场的一天中各时间到达航班乘客数据和机场蓄车池中出租车数量的实时数据,运用SPSS软件的K-means聚类算法对机场到达航班乘客进行时间上的分类,比较不同时间段下对机场出租车的数量变化。
In recent years,with the continuous development of transportation,more and more people take planes,and taxi has become one of the main means of transportation for passengers to leave the airport.In order to study the flow of airport taxis,the decision-making model of taxi drivers at the airport is established by looking for analysis indicators to help the airport make reasonable plans for taxi passengers and airport taxis.In this paper,by collecting the data of passengers arriving at different times of the day at the airport and the real-time data of the number of taxis in the airport car storage pool,the K-means clustering algorithm of SPSS software is used to classify the passengers arriving at the airport in time,and the changes of the number of airport taxis in different time periods are compared.
出处
《科技创新与应用》
2020年第16期22-24,共3页
Technology Innovation and Application