{"title":"评估运输管理系统的预测分析供应商","authors":"A. Nagy, J. Tick","doi":"10.1109/SISY.2017.8080557","DOIUrl":null,"url":null,"abstract":"Most of transport corporations today already use some business intelligence solutions. However, using of advanced data mining methods may result in higher efficiency, increased level of travel experience. This paper briefly review the potential vendors and technologies to probably select the best possible predictive analytics method for transport management purposes.","PeriodicalId":352891,"journal":{"name":"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Review of predictive analytics vendors for transport management systems\",\"authors\":\"A. Nagy, J. Tick\",\"doi\":\"10.1109/SISY.2017.8080557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most of transport corporations today already use some business intelligence solutions. However, using of advanced data mining methods may result in higher efficiency, increased level of travel experience. This paper briefly review the potential vendors and technologies to probably select the best possible predictive analytics method for transport management purposes.\",\"PeriodicalId\":352891,\"journal\":{\"name\":\"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SISY.2017.8080557\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISY.2017.8080557","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Review of predictive analytics vendors for transport management systems
Most of transport corporations today already use some business intelligence solutions. However, using of advanced data mining methods may result in higher efficiency, increased level of travel experience. This paper briefly review the potential vendors and technologies to probably select the best possible predictive analytics method for transport management purposes.