Traffic 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.
|Name|| AIP Conference Proceedings|
|Conference||International Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007|
|Period||25/09/07 → 30/09/07|
- partial least square regression; kernel; proximity; K nearest neighbors; Nonparametric classification; radar cross section; fast Fourier transform (FFT)