摘要
根据大连市公交IC卡的历史数据绘制公交线路客流曲线,采用有序聚类Fisher算法划分公交峰值区间,在具有典型特征的峰值区间内进行有针对性的公交客流调查,可得到实际客流数据样本。通过将公交IC卡客流数据与随车客流调查数据相结合,建立不同峰值条件下预测客流的回归方程,可实现对不同峰值区间内总体客流量的预测。
Administrative Office of Dalian, Abstract： By taking out historical data from Dalian public transit intelligent card database, the curve of passenger flow volume is introduced. With Fisher＇s sequence clustering method, the daily transit peak value interval is obtained. Then, a pointed passenger flow volume survey for transit peak value interval with typical characteristics is carried on to get data sample of practical passenger flow volume. By combining the passenger flow volume data based on the public transit intelligent card with which based on passenger flow survey, the regression equations for passenger flow volume forecasting in different cases of transit peak value interval are established in order to forecast the total passenger flow volume in different transit peak value intervals.
出处
《交通标准化》
2009年第9期115-119,共5页
Communications Standardization
基金
国家自然科学基金资助项目(70571007)
关键词
公交IC卡
有序聚类Fisher算法
公交客流调查
客流预测
public transit intelligent card（IC）
Fisher＇s sequence clustering method
passenger flow survey
passenger flow volume forecasting
