{"title":"基于车联网大数据的细分市场模型研究","authors":"Huajun Wang, Liang Yang, Wenbin Wang, Xiaolin Zhang","doi":"10.1109/CACML55074.2022.00096","DOIUrl":null,"url":null,"abstract":"At present, there are many problems in China's commercial vehicle enterprise, such as large subjective judgment deviation and lack of scientific calculation method. In order to solve the above problems, this paper takes the data of internet of vehicles in June 2021 collected by heavy truck of a commercial vehicle based on GB/T 17691–2018 as the experimental sample, and mining the scientific calculation model and system of commercial vehicle market segment by using algorithms such as parking point analysis and processing, word segmentation processing, DBSCAN clustering and Apriori association. The experimental results show that the effectiveness and accuracy of the model are 98.18% and 94.4% respectively. At the same time, we designed a 100,000-magnitude platform technology scheme, which reached the enterprise-level usability requirements and verified the feasibility of the research method in this paper.","PeriodicalId":137505,"journal":{"name":"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model Study of Segment Market on Internet of Vehicles Big Data\",\"authors\":\"Huajun Wang, Liang Yang, Wenbin Wang, Xiaolin Zhang\",\"doi\":\"10.1109/CACML55074.2022.00096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, there are many problems in China's commercial vehicle enterprise, such as large subjective judgment deviation and lack of scientific calculation method. In order to solve the above problems, this paper takes the data of internet of vehicles in June 2021 collected by heavy truck of a commercial vehicle based on GB/T 17691–2018 as the experimental sample, and mining the scientific calculation model and system of commercial vehicle market segment by using algorithms such as parking point analysis and processing, word segmentation processing, DBSCAN clustering and Apriori association. The experimental results show that the effectiveness and accuracy of the model are 98.18% and 94.4% respectively. At the same time, we designed a 100,000-magnitude platform technology scheme, which reached the enterprise-level usability requirements and verified the feasibility of the research method in this paper.\",\"PeriodicalId\":137505,\"journal\":{\"name\":\"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CACML55074.2022.00096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACML55074.2022.00096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model Study of Segment Market on Internet of Vehicles Big Data
At present, there are many problems in China's commercial vehicle enterprise, such as large subjective judgment deviation and lack of scientific calculation method. In order to solve the above problems, this paper takes the data of internet of vehicles in June 2021 collected by heavy truck of a commercial vehicle based on GB/T 17691–2018 as the experimental sample, and mining the scientific calculation model and system of commercial vehicle market segment by using algorithms such as parking point analysis and processing, word segmentation processing, DBSCAN clustering and Apriori association. The experimental results show that the effectiveness and accuracy of the model are 98.18% and 94.4% respectively. At the same time, we designed a 100,000-magnitude platform technology scheme, which reached the enterprise-level usability requirements and verified the feasibility of the research method in this paper.