基于机器学习的公交站间运行时间幂律分布分析  

Power Law Distribution Analysis of Running Time Between Bus Stations Based on Machine Learning

作　　者：徐文进[1] 寻晴晴 周笛 XU Wen-Jin;XUN Qing-Qing;ZHOU Di(School of Information Science and Technology,Qingdao University of Science and Technology,Qingdao 266061,China;Unit 91049,PLA Northern Theater Command,Qingdao 266000,China)

机构地区：[1]青岛科技大学信息科学技术学院,青岛266061 [2]解放军北部战区91049部队,青岛266000

出　　处：《计算机系统应用》2019年第12期177-183,共7页Computer Systems & Applications

基　　金：2018年度山东省重点研发计划(2018GGX105005)~~

摘　　要：为了解决城市交通拥挤问题,国家提倡乘坐公共交通出行,使用公交智能卡的出行变的普遍了.目前,对于城际公交智能卡出行产生的数据,很少有研究公交站间运行的时间.因此,提出了基于机器学习技术公交站间运行时间幂律分布的分析;运用分站算法对城市公交进行分站,获得公交车在相邻两站的运行时间;并且对时间间隔数据进行了线性拟合.运用南方某城市和北方某城市的两个数据集,结果表明公交车运行时间间隔符合幂指数分布;公交车运行的时间间隔符合人类行为动力学.In order to solve the problem of urban traffic congestion,the state advocates travelling by public transportation,and the use of bus smart cards has become more common.At present,for the data generated by intercity bus smart card travel,there is very little research on the time between bus stations.Therefore,the power-law distribution analysis of running time between bus stations based on machine learning technology is proposed.The station algorithm is used to divide the bus stations in the city,and the running time of the bus in the two adjacent stations is obtained.The time interval data were fitted linearly.Using two data sets from a city in South China and a city in North China,the results show that the bus running time interval is in accordance with the power exponential distribution;the time interval of bus operation is in line with human behavior dynamics.

关 键 词：机器学习 公交智能卡 分站算法 人类行为动力学 幂指数分布 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] U491.17[自动化与计算机技术—控制科学与工程]