The Prediction of Road-Accident Risk through Data Mining: A Case Study from Setubal, Portugal

被引：3
|
作者：
Dias, David [1 ,2 ]
Silva, Jose Silvestre [1 ,3 ,4 ]
Bernardino, Alexandre [2 ,5 ]
机构：
[1] Portuguese Mil Acad, Rua Gomes Freire, P-1169203 Lisbon, Portugal
[2] Univ Lisbon, Inst Super Tecn, P-1049001 Lisbon, Portugal
[3] Mil Acad Res Ctr CINAMIL, Rua Gomes Freire, P-1169203 Lisbon, Portugal
[4] Lab Instrumentat Biomed Engn & Radiat Phys LIBPhy, P-3000370 Coimbra, Portugal
[5] Inst Syst & Robot ISR IST, P-1049001 Lisbon, Portugal
来源：
INFORMATICS-BASEL | 2023年 / 10卷 / 01期
关键词：
risk prediction; road accidents; supervised classification; classical methods; deep neural networks; PRECIPITATION;
D O I：
10.3390/informatics10010017
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This work proposes a tool to predict the risk of road accidents. The developed system consists of three steps: data selection and collection, preprocessing, and the use of mining algorithms. The data were imported from the Portuguese National Guard database, and they related to accidents that occurred from 2019 to 2021. The results allowed us to conclude that the highest concentration of accidents occurs during the time interval from 17:00 to 20:00, and that rain is the meteorological factor with the greatest effect on the probability of an accident occurring. Additionally, we concluded that Friday is the day of the week on which more accidents occur than on other days. These results are of importance to the decision makers responsible for planning the most effective allocation of resources for traffic surveillance.
引用
收藏
页数：15
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