Data Mining Method of Road Transportation Management Information Based on Rough Set and Association Rule

doi:10.3969/j.issn.1000-565X.2014.02.020

Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (2): 132-138.doi: 10.3969/j.issn.1000-565X.2014.02.020

• Traffic & Transportation Engineering • Previous Articles Next Articles

Data Mining Method of Road Transportation Management Information Based on Rough Set and Association Rule

Zheng Xiao- feng Wang Shu

School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China

Received:2013-09-25 Revised:2013-11-21 Online:2014-02-25 Published:2014-01-02
Contact: 郑晓峰(1977-)，男，博士生，工程师，主要从事道路交通运输管理研究． E-mail:bobcraft@163.com
About author:郑晓峰(1977-)，男，博士生，工程师，主要从事道路交通运输管理研究．
Supported by:
国家自然科学基金资助项目(61174184);广州市科技支撑计划项目(2011J4300045)

Abstract

Abstract:

As the data of the road transportation management information system are mostly inconsistent,impreciseand incomplete,a novel data mining method,which combines the rough set analysis with the classical associationrule,is proposed based on the system induction idea and the attribute reduction method of the rough set theory.Then,the relationship among the rule number,the support degree and the confidence is analyzed by using therough set method,and the reliability and validity of the proposed method is verified through a case study.The re-sults indicate that the proposed method can realize an attribute reduction of 33.3%,which means that the methodis effective in solving the problems existing in the real road transportation management system.

Key words: road transportation, management information, rough set, association rule, data mining

CLC Number:

U495

Zheng Xiao- feng Wang Shu. Data Mining Method of Road Transportation Management Information Based on Rough Set and Association Rule[J]. Journal of South China University of Technology (Natural Science Edition), 2014, 42(2): 132-138.

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Data Mining Method of Road Transportation Management Information Based on Rough Set and Association Rule

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