Journal of Northeastern University ›› 2004, Vol. 25 ›› Issue (10): 938-941.DOI: -

• OriginalPaper • Previous Articles     Next Articles

Mining association rule on rough entropy basis in detecting escapes from traffic accidents

Zhao, Hai (1); Chen, Yan (2); Zhang, De-Gan (1); Zhang, Xiao-Dan (1)   

  1. (1) Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China; (2) Dept. of Mgmt., Dalian Maritime Affairs Univ., Dalian 116000, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2004-10-15 Published:2013-06-24
  • Contact: Zhao, H.
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Abstract: Traditional data mining algorithms have unavoidably errors arising from additional man-made uncertain factors in dealing with multi-source information. A new mining method called association rule is therefore proposed basis in view of rough set theory, with another method specially designed to assess it. Method from historical data of the crimes escaping from traffic accidents in a designed way, the association rules will provide an efficient and practical means for the police to detect the crimes escaping from traffic accidents. Some applications have exemplified the effectiveness of the method proposed.

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