{"title":"改进时空DS证据理论在车辆识别中的应用","authors":"Yun Lin, Gao Lipeng, Yibing Li, Si Xicai","doi":"10.1109/PRIMEASIA.2009.5397368","DOIUrl":null,"url":null,"abstract":"In this paper, it takes advantage of evidence theory to fuse the data with multi-sensors and multi-measuring periods. It discusses three kinds of fusion structures: concentrated fusion, distributed fusion without feedback and distributed fusion with feedback. In the application of vehicle type distinguishing, through theoretical analysis and simulation results, the paper gets the conclusion that when the data provided by the sensors is not very accurate (even wrong), the distributed fusion without feedback can get the highest rate of correct result, the distributed fusion with feedback follows and the concentrated fusion is the worst.","PeriodicalId":217369,"journal":{"name":"2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The application of improving space-time DS evidence theory in distinguishing vehicle\",\"authors\":\"Yun Lin, Gao Lipeng, Yibing Li, Si Xicai\",\"doi\":\"10.1109/PRIMEASIA.2009.5397368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, it takes advantage of evidence theory to fuse the data with multi-sensors and multi-measuring periods. It discusses three kinds of fusion structures: concentrated fusion, distributed fusion without feedback and distributed fusion with feedback. In the application of vehicle type distinguishing, through theoretical analysis and simulation results, the paper gets the conclusion that when the data provided by the sensors is not very accurate (even wrong), the distributed fusion without feedback can get the highest rate of correct result, the distributed fusion with feedback follows and the concentrated fusion is the worst.\",\"PeriodicalId\":217369,\"journal\":{\"name\":\"2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRIMEASIA.2009.5397368\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRIMEASIA.2009.5397368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of improving space-time DS evidence theory in distinguishing vehicle
In this paper, it takes advantage of evidence theory to fuse the data with multi-sensors and multi-measuring periods. It discusses three kinds of fusion structures: concentrated fusion, distributed fusion without feedback and distributed fusion with feedback. In the application of vehicle type distinguishing, through theoretical analysis and simulation results, the paper gets the conclusion that when the data provided by the sensors is not very accurate (even wrong), the distributed fusion without feedback can get the highest rate of correct result, the distributed fusion with feedback follows and the concentrated fusion is the worst.