M. S. Hazaa, Redhwan M. A. Saad, Mohammed A. Alnaklani
{"title":"利用数据挖掘技术预测也门ibb省交通事故严重程度","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":"{\"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}","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}
PREDICTION OF TRAFFIC ACCIDENT SEVERITY USING DATA MINING TECHNIQUES IN IBB PROVINCE, YEMEN
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.