{"title":"基于神经网络和遗传算法的公路交通预测","authors":"WangYan, Wang Hua, Xiang Limin","doi":"10.1109/ICVES.2005.1563643","DOIUrl":null,"url":null,"abstract":"Traffic prediction method and the correctness of its result are very important for vehicle management, so highway traffic prediction method has a close relationship with vehicle safety. Traditional prediction method has some problems, such as low accuracy and efficiency, so we present a model based on the combination of genetic algorithms and artificial neural network, and by improving these two algorithms in the process of implementation, increase further the accuracy and efficiency of the model. At last, some experiments are made to prove its fine performance.","PeriodicalId":443433,"journal":{"name":"IEEE International Conference on Vehicular Electronics and Safety, 2005.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Highway traffic prediction with neural network and genetic algorithms\",\"authors\":\"WangYan, Wang Hua, Xiang Limin\",\"doi\":\"10.1109/ICVES.2005.1563643\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traffic prediction method and the correctness of its result are very important for vehicle management, so highway traffic prediction method has a close relationship with vehicle safety. Traditional prediction method has some problems, such as low accuracy and efficiency, so we present a model based on the combination of genetic algorithms and artificial neural network, and by improving these two algorithms in the process of implementation, increase further the accuracy and efficiency of the model. At last, some experiments are made to prove its fine performance.\",\"PeriodicalId\":443433,\"journal\":{\"name\":\"IEEE International Conference on Vehicular Electronics and Safety, 2005.\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Vehicular Electronics and Safety, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVES.2005.1563643\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Vehicular Electronics and Safety, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVES.2005.1563643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Highway traffic prediction with neural network and genetic algorithms
Traffic prediction method and the correctness of its result are very important for vehicle management, so highway traffic prediction method has a close relationship with vehicle safety. Traditional prediction method has some problems, such as low accuracy and efficiency, so we present a model based on the combination of genetic algorithms and artificial neural network, and by improving these two algorithms in the process of implementation, increase further the accuracy and efficiency of the model. At last, some experiments are made to prove its fine performance.