Using Decision Trees to extract Decision Rules from Police Reports on Road Accidents

被引：24

作者：

Griselda, Lopez ^{[1
]}

Juan, de Ona ^{[1
]}

Joaquin, Abellan ^{[2
]}

机构：

[1] Univ Granada, Dept Civil Engn, ETSI Caminos, TRYSE Res Grp, E-18071 Granada, Spain

[2] Univ Granada, ETSI Infomat, Dept Comp Sci & Artificial Intelligence, E-18071 Granada, Spain

来源：

SIIV-5TH INTERNATIONAL CONGRESS - SUSTAINABILITY OF ROAD INFRASTRUCTURES 2012 | 2012年 / 53卷

关键词：

DRIVER INJURY SEVERITY; LOGISTIC-REGRESSION; MODELS;

D O I：

10.1016/j.sbspro.2012.09.864

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

The World Health Organization (WHO) considers that traffic accidents are major public health problem worldwide, for this reason safety managers try to identify the main factors affecting the severity as consequence of road accidents. In order to identify these factors, in this paper, Data Mining (DM) techniques such as Decision Trees (DTs), have been used. A dataset of traffic accidents on rural roads in the province of Granada (Spain) have been analyzed. DTs allow certain decision rules to be extracted. These rules could be used in future road safety campaigns and would enable managers to implement certain priority actions. (C) 2012 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of SIIV2012 Scientific Committee

引用

页码：106 / 114

页数：9

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