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System Development & Application
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829-832,837

Research on railway scattered freight customer churn prediction based on parallel C4.5 decision tree algorithm

Zhang Bin
Peng Qiyuan
Liu Fanxiao
School of Transportation & Logistics, Southwest Jiaotong University, Chengdu 610031, China

Abstract

In order to improve the accuracy and efficiency of customer churn prediction of railway scattered freight, according to the loss characteristics of railway scattered freight customers, this paper proposed a customer churn identification method based on CDL model. On this basis, facing the problem of big data, it proposed a C4.5 decision tree customer churn prediction model based on Hadoop parallel framework. Simulation results show that the model has good accuracy and predictive ability, and as the number of samples increases, obviously improves the efficiency of Hadoop parallel framework, and doesn't affect the accuracy and prediction ability of churn prediction model.

Foundation Support

中国铁路总公司科研计划重大课题(2016X008-J)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.09.0912
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 3
Section: System Development & Application
Pages: 829-832,837
Serial Number: 1001-3695(2019)03-037-0829-04

Publish History

[2019-03-05] Printed Article

Cite This Article

张斌, 彭其渊, 刘帆洨. 基于并行C4.5的铁路零散白货客户流失预测研究 [J]. 计算机应用研究, 2019, 36 (3): 829-832,837. (Zhang Bin, Peng Qiyuan, Liu Fanxiao. Research on railway scattered freight customer churn prediction based on parallel C4.5 decision tree algorithm [J]. Application Research of Computers, 2019, 36 (3): 829-832,837. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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