PREDICTION OF TRAFFIC ACCIDENT SEVERITY USING DATA MINING TECHNIQUES IN IBB PROVINCE, YEMEN

M. S. Hazaa, Redhwan M. A. Saad, Mohammed A. Alnaklani
{"title":"PREDICTION OF TRAFFIC ACCIDENT SEVERITY USING DATA MINING TECHNIQUES IN IBB PROVINCE, YEMEN","authors":"M. S. Hazaa, Redhwan M. A. Saad, Mohammed A. Alnaklani","doi":"10.15282/IJSECS.5.1.2019.6.0056","DOIUrl":null,"url":null,"abstract":"Traffic accidents are the leading causes beyond death; it is the concern of most countries that strive for finding radical solutions to this problem. There are several methods used in the process of forecasting traffic accidents such as classification, assembly, association, etc. This paper surveyed the latest studies in the field of traffic accident prediction; the most important tools and algorithms were used in the prediction process such as Back- propagation Neural Networks and the decision tree. In addition, this paper proposed a model for predicting traffic accidents based on dataset obtained from the Directorate General of Traffic Statistics, Ibb, Yemen.","PeriodicalId":31240,"journal":{"name":"International Journal of Software Engineering and Computer Systems","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Software Engineering and Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15282/IJSECS.5.1.2019.6.0056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Traffic accidents are the leading causes beyond death; it is the concern of most countries that strive for finding radical solutions to this problem. There are several methods used in the process of forecasting traffic accidents such as classification, assembly, association, etc. This paper surveyed the latest studies in the field of traffic accident prediction; the most important tools and algorithms were used in the prediction process such as Back- propagation Neural Networks and the decision tree. In addition, this paper proposed a model for predicting traffic accidents based on dataset obtained from the Directorate General of Traffic Statistics, Ibb, Yemen.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用数据挖掘技术预测也门ibb省交通事故严重程度
交通事故是除死亡以外的主要原因;这是大多数国家所关心的问题,它们努力寻求彻底解决这一问题的办法。在交通事故预测过程中,常用的方法有分类法、集合法、关联法等。本文综述了交通事故预测领域的最新研究进展;在预测过程中使用了最重要的工具和算法,如反向传播神经网络和决策树。此外,本文还提出了一个基于也门交通统计总局数据集的交通事故预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
14
期刊最新文献
The Mobile Augmented Reality Application for Improving Learning of Electronic Component Module in TVET A Systematic Mapping on Android-based Platform for Smart Inventory System Sentiment Classification of Tweets with Explicit Word Negations and Emoji Using Deep Learning Protocol Efficiency Using Multiple Level Encoding in Quantum Secure Direct Communication Protocol SECURING IOT HEALTHCARE APPLICATIONS AND BLOCKCHAIN: ADDRESSING SECURITY ATTACKS
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1