A Review On Road Accident Data Analysis Using Data Mining Techniques

被引:0
|
作者
Kasbe, Prajakta S. [1 ]
Sakhare, Apeksha V. [1 ]
机构
[1] GH Raisoni Coll Engn, Comp Sci & Engn, Nagpur, Maharashtra, India
关键词
Data Mining; accident analysis; K-mean; self organizing-map(SOM); clustering;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Road accident analysis plays an important role in transportation system. This paper shows a survey of road accident analysis methods in data mining. In the data mining there is no. of techniques available for clustering and classification, from those techniques k-mean, association rule, SVM, Weka tool was used in previously research for road accident analysis. In our daily life there are no. of accident increases and it is big problem to us because no. of people death and injured for that improve the road transportation system is needed. In this research self organization map (SOM) is used for find a no. of pattern to analysis the road accident data which help to find prediction of accident reasons and improve the accuracy of analysis compare to k-means clustering algorithm. With the help of SOM, clusters are created and analyze them. Self Organizing map method is based on neural network, it is used as an unsupervised learning method. It will help to improve analysis accuracy.
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页数:5
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