{"title":"数据挖掘算法在智能交通中的应用研究","authors":"Weifang Zhai, Yiran Jiang, Song Ji","doi":"10.4018/IJAPUC.2019040101","DOIUrl":null,"url":null,"abstract":"Nowadays, in the field of intelligent transportation, data mining technology has been applied more and more widely. Data mining technology can find valuable data from amongst massive traffic data and analyze traffic conditions according to actual traffic conditions. In order to improve the management and control level of ITMS, effective information can be queried from various query conditions, models suitable for various traffic situations can be found, analyzed and predicted, and accurate information can be provided to traffic managers for decision-making. This article mainly studies the data mining algorithm in intelligent transportation, in order to provide practical reference for the application and research of urban traffic big data technology.","PeriodicalId":145240,"journal":{"name":"Int. J. Adv. Pervasive Ubiquitous Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on the Application of Data Mining Algorithms in Intelligent Transportation\",\"authors\":\"Weifang Zhai, Yiran Jiang, Song Ji\",\"doi\":\"10.4018/IJAPUC.2019040101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, in the field of intelligent transportation, data mining technology has been applied more and more widely. Data mining technology can find valuable data from amongst massive traffic data and analyze traffic conditions according to actual traffic conditions. In order to improve the management and control level of ITMS, effective information can be queried from various query conditions, models suitable for various traffic situations can be found, analyzed and predicted, and accurate information can be provided to traffic managers for decision-making. This article mainly studies the data mining algorithm in intelligent transportation, in order to provide practical reference for the application and research of urban traffic big data technology.\",\"PeriodicalId\":145240,\"journal\":{\"name\":\"Int. J. Adv. Pervasive Ubiquitous Comput.\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Adv. Pervasive Ubiquitous Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJAPUC.2019040101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Adv. Pervasive Ubiquitous Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJAPUC.2019040101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on the Application of Data Mining Algorithms in Intelligent Transportation
Nowadays, in the field of intelligent transportation, data mining technology has been applied more and more widely. Data mining technology can find valuable data from amongst massive traffic data and analyze traffic conditions according to actual traffic conditions. In order to improve the management and control level of ITMS, effective information can be queried from various query conditions, models suitable for various traffic situations can be found, analyzed and predicted, and accurate information can be provided to traffic managers for decision-making. This article mainly studies the data mining algorithm in intelligent transportation, in order to provide practical reference for the application and research of urban traffic big data technology.