摘要
了解居民公交出行乘车特征、掌握公交出行客流规律是公交规划和运营决策的基础。为了研究不同时段居民公交乘车的分布特性,以北京市分段计价线路公交IC刷卡数据为依据,基于数据挖掘工具分析了居民公交出行乘车的距离特性,并对乘车距离分布进行曲线拟合,结果表明:北京市居民公交乘车距离服从威布尔分布,在置信水平为95%的条件下,平方误差和小于0.01,拟合优度在0.97以上。
Knowing the characteristics of transit travel is the basis for transit planning and operational decision-making.This paper analyzes the characteristics of transit travel based on data mining tools,using segmented pricing line bus IC card data in Beijing in order to study the different periods of the resident bus travel distribution features.The travel station distribution results show that the number of transit travel stops for Beijing residents obeys Weibull distribution.At the 95% condition of confidence level,the sum of squared error（SSE） is less than 0.01,while the goodness of fit is more than 0.97.
出处
《交通信息与安全》
2012年第6期87-89,99,共4页
Journal of Transport Information and Safety
基金
国家"863"高技术研究发展计划基金项目(批准号:2008AA11Z202)资助
关键词
公交IC卡
乘车距离
公交出行特征
数据挖掘
transit IC card
travel distance
transit travel characteristics
data mining
