标题:Traffic accident data mining based on association rules theory
作者:Li, Meiying ;Li, Meiye ;Hu, Xiaoxia ;Li, Yu
通讯作者:Li, Meiying
作者机构:[Li, M] School of Control Science and Engineering, Shandong University, Jinan, 250061, China, School of Control Science and Engin., Shandong Universit 更多
会议名称:3rd International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2018
会议日期:15 September 2018 through 16 September 2018
来源:Frontiers in Artificial Intelligence and Applications
出版年:2019
卷:314
页码:330-340
DOI:10.3233/978-1-61499-939-3-330
关键词:Association rules; Data mining; SQL Server; Traffic accidents
摘要:Traffic accident is one of the most important topics in traffic field, and traffic accidents happened in China caused thousands of casualties every year. If we still adopt traditional methods to analyze, we will miss lots of information. As for big data analysis, association rules theory, as a new method of data analysis, has been widely used in various fields. Association rules theory is applied to analyze traffic accidents in this paper. The multi-dimensional data warehouse and star schema are designed in software to store traffic accident data of Guiyang, then the association rules mining model is established and strong association rules in accidents will be obtained. Finally, for these strong association rules in traffic accidents, preventive suggestions will be put forward. © 2019 The authors and IOS Press. All rights reserved.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060878910&doi=10.3233%2f978-1-61499-939-3-330&partnerID=40&md5=45864fc96f3faf8f9a3bf9298ec56a84
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