Road traffic accident data mining based on grey relational clustering

被引：0

作者：

Liu Y. ^{[1
]}

Xu H. ^{[2
]}

Zhang C. ^{[1
]}

Shi X.D. ^{[3
]}

Patnaik S. ^{[4
]}

机构：

[1] Cloud Computing and Big Data Institute, Henan University of Economics and Law, Henan, Zhengzhou

[2] Henan Key Laboratory of Ecological Environment Protection and Restoration of the Yellow River Basin, Yellow River Institute of Hydraulic Research, Henan, Zhengzhou

[3] School of 'E-commerce and Logistics Management, Henan University of Economics and Law, Zhengzhou

[4] Department of Computer Science and Engineering, SOA University, Bhubaneswar

来源：

Advances in Transportation Studies | 2023年 / 3卷 / Special issue期

关键词：

accident data mining; EM algorithm; fault tree analysis; grey relational clustering; road traffic;

D O I：

10.53136/979122180922010

中图分类号：

学科分类号：

摘要：

Data mining can effectively identify and discover the patterns and inherent laws of accident data. The paper proposes a road traffic accident data mining method based on grey relational clustering. Determine the key influencing factors of road traffic accidents through fault tree analysis method, and achieve accurate quantification of road traffic accident data. Extract the features of road traffic accident data based on EM algorithm. Set the grey relationship analysis factor for road traffic accident data, create a sequence of behavioral feature data, and determine the grey relationship sequence by the operator. Using whitening weight functions to cluster the features of accident data, classify data with consistent features, and achieve road traffic accident data mining. The experimental results show that the designed method has good sensitivity and high grey correlation coefficient in road traffic accident data mining, indicating the feasibility of this method. © 2023, Aracne Editrice. All rights reserved.

引用

页码：113 / 124

页数：11

共 50 条

[41] Feature extraction algorithm of clustering based on grey relational theory
Lu, Feng
Huang, Jin-Quan
[J]. Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2012, 32 (04): : 872 - 876
[42] Divisive hierarchical clustering algorithm based on grey relational measure
Chen T.
Jin W.
Li J.
[J]. Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University, 2010, 45 (02): : 296 - 301
[43] Vehicle Safety Device (Airbag) Specific Classification of Road Traffic Accident Patterns through Data Mining Techniques
Shanthi, S.
Ramani, R. Geetha
[J]. ADVANCES IN COMPUTING AND INFORMATION TECHNOLOGY, VOL 2, 2013, 177 : 433 - +
[44] Classifier Prediction Evaluation in Modeling Road Traffic Accident Data
Ramani, R. Geetha
Shanthi, S.
[J]. 2012 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2012, : 293 - 296
[45] GIS based urban road traffic accident analysis
Gao, D. Q.
Li, Q. Q.
Li, L. Y.
[J]. 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 3, 2008, : 614 - 618
[46] Risk analysis of road traffic accidents based on improved data mining method
Feng T.
Gao T.
[J]. International Journal of Simulation and Process Modelling, 2022, 18 (04) : 253 - 266
[47] Collaborative mining method of traffic accident data based on decision tree and association rules
Liu F.H.
[J]. Advances in Transportation Studies, 2023, 1 (Special Issue): : 73 - 86
[48] Analyzing Highway Road Accident Characteristic Using Data Mining
Ilham, Muhammad Yogi
Suijandari, Isti
Laoh, Enrico
[J]. 2020 5TH INTERNATIONAL WORKSHOP ON BIG DATA AND INFORMATION SECURITY (IWBIS 2020), 2020, : 19 - 23
[49] Data mining model of regional road traffic accidents based on bat algorithm
Yang B.
[J]. Advances in Transportation Studies, 2022, 2 (Special issue): : 113 - 122
[50] A Hybrid Algorithm of Traffic Accident Data Mining on Cause Analysis
Xi, Jianfeng
Gao, Zhenhai
Niu, Shifeng
Ding, Tongqiang
Ning, Guobao
[J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013

← 1 2 3 4 5 →