To divide the passenger flow’s period of intercity railway scientifically and accurately, and promote the rapid development of intercity railway in each major urban agglomeration in our country, this study analyzes the problem division of passenger flow’s period of intercity railway, combines the dynamic change rule like bus of intercity railway’s passenger flow and the advantages of K-means clustering algorithm. Using K-means clustering algorithm to analyze the intercity ticket data of Jiujiang-Nanchang, distinguishes the high and low peaks in different operation periods of intercity railway, and divides the passenger flow’s period of intercity railway accurately and reasonably. this study is not only helpful for the railway departments to compile the operation plan and dispatching plan of intercity railway reasonably, but also plays a very important role in improving transportation capacity, service quality and the development of informatization and intelligence of intercity railway operation.

CICTP