{"title":"基于交通大数据的工作居所标注算法及应用","authors":"Jie Wang, Yunyao Zhou","doi":"10.2991/ICMEIT-19.2019.50","DOIUrl":null,"url":null,"abstract":"Congestion in urban makes too many commuters choose public transport for traveling. A large number of public transportation travel data can accurately calculate workplace and residence of the regular passengers. The label of workplace and residence helps to analyze urban migration and the distribution of workplace and residence.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algorithm and Application for Labeling Workplace and Residence based on Traffic Big Data\",\"authors\":\"Jie Wang, Yunyao Zhou\",\"doi\":\"10.2991/ICMEIT-19.2019.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Congestion in urban makes too many commuters choose public transport for traveling. A large number of public transportation travel data can accurately calculate workplace and residence of the regular passengers. The label of workplace and residence helps to analyze urban migration and the distribution of workplace and residence.\",\"PeriodicalId\":223458,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/ICMEIT-19.2019.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algorithm and Application for Labeling Workplace and Residence based on Traffic Big Data
Congestion in urban makes too many commuters choose public transport for traveling. A large number of public transportation travel data can accurately calculate workplace and residence of the regular passengers. The label of workplace and residence helps to analyze urban migration and the distribution of workplace and residence.
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