The research of railway transport market subdivision based on data mining technology

Author

Tian, Ya ; Chen, Jiajuan ; Wang, Xuebing

Author_Institution

Sch. of Traffic & Transp., Beijing Jiaotong Univ., Beijing

Volume

1

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

147

Lastpage

152

Abstract

Facing to the characters of railway transport industry, parameters of railway freight market customer subdivision were presented; clustering model K-Means was established for market subdivision. The algorithm of K-Means was modified by using square error and objective function. Actual experiment of railway transport market subdivision is done based on Clementine 8.0 platform, and the features of various submarkets acquired form the experiment was analyzed and described.

Keywords

data mining; freight handling; goods distribution; railway industry; K-Means algorithm; data mining technology; railway freight market customer subdivision; railway transport industry; railway transport market research; square error function; Clustering algorithms; Data mining; Economic forecasting; Information analysis; Mining industry; Modems; Rail transportation; Road transportation; Scattering; Traffic control; Cluster analysis; Freight transportation; Market Subdivision; Railway;

fLanguage

English

Publisher

ieee

Conference_Titel

Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2012-4

Electronic_ISBN

978-1-4244-2013-1

Type

conf

DOI

10.1109/SOLI.2008.4686381

Filename

4686381