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dc.contributor.authorJou, Yow-Jenen_US
dc.contributor.authorLu, Yung-Tsaien_US
dc.contributor.authorLan, Chien-Lunen_US
dc.contributor.authorLee, Hsiaen_US
dc.date.accessioned2014-12-08T15:11:18Z-
dc.date.available2014-12-08T15:11:18Z-
dc.date.issued2007en_US
dc.identifier.isbn978-0-7354-0476-2en_US
dc.identifier.issn0094-243Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/8679-
dc.description.abstractTraffic congestion is a serious and general problem in our daily life. Real time vehicle information is essential to the advanced traffic management. The recognition and statistics of traffic flow among different types of vehicles would be contributive to improve traffic block. This paper considers the dataset recorded by the radar microwave detector with the intensity of reflecting waves and the types of vehicles. The data is treated as functional data and then classification would be proposed to be performed by nonparametfic discrimination of functional data with three forms of Proximity. The proximity with lower misclassification rate would be adopted for the data. The results show that the misclassification rate is pretty satisfactory if the number of groups is two and as the number of group increases the misclassification rate increases as expected.en_US
dc.language.isoen_USen_US
dc.subjectpartial least square regressionen_US
dc.subjectkernelen_US
dc.subjectproximityen_US
dc.subjectK nearest neighborsen_US
dc.subjectNonparametric classificationen_US
dc.subjectradar cross sectionen_US
dc.subjectfast Fourier transform (FFT)en_US
dc.titleSignal recognition by nonparametric discrimination of functional data for vehicle transportation systemen_US
dc.typeProceedings Paperen_US
dc.identifier.journalCOMPUTATION IN MODERN SCIENCE AND ENGINEERING VOL 2, PTS A AND Ben_US
dc.citation.volume2en_US
dc.citation.spage980en_US
dc.citation.epage983en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000252602900243-
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