{"title":"利用机器学习预测道路事故","authors":"Dr. M. Hemalatha, S. Dhuwaraganath","doi":"10.32628/ijsrst52411284","DOIUrl":null,"url":null,"abstract":"Road accidents are a significant cause of fatalities and injuries worldwide. Predicting road accidents is crucial for implementing preventive measures and saving lives. This paper presents a deep learning-based road accident prediction system utilizing various factors such as speed, traffic condition, weather, and more. By leveraging publicly available datasets and external data sources, the model aims to accurately predict road accidents, ultimately contributing to enhancing road safety.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Road Accident Prediction Using Machine Learning\",\"authors\":\"Dr. M. Hemalatha, S. Dhuwaraganath\",\"doi\":\"10.32628/ijsrst52411284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Road accidents are a significant cause of fatalities and injuries worldwide. Predicting road accidents is crucial for implementing preventive measures and saving lives. This paper presents a deep learning-based road accident prediction system utilizing various factors such as speed, traffic condition, weather, and more. By leveraging publicly available datasets and external data sources, the model aims to accurately predict road accidents, ultimately contributing to enhancing road safety.\",\"PeriodicalId\":14387,\"journal\":{\"name\":\"International Journal of Scientific Research in Science and Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Scientific Research in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32628/ijsrst52411284\",\"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 Scientific Research in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32628/ijsrst52411284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Road accidents are a significant cause of fatalities and injuries worldwide. Predicting road accidents is crucial for implementing preventive measures and saving lives. This paper presents a deep learning-based road accident prediction system utilizing various factors such as speed, traffic condition, weather, and more. By leveraging publicly available datasets and external data sources, the model aims to accurately predict road accidents, ultimately contributing to enhancing road safety.
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